Jean-Yves Audibert
email: audibert@certis.enpc.fr

Rémi Munos
email: remi.munos@inria.fr

Csaba Szepesvári
email: szepesva@cs.ualberta.ca

Tuning bandit algorithms in stochastic environments

Algorithms based on upper-confidence bounds for balancing exploration and exploitation are gaining popularity since they are easy to implement, efficient and effective. In this paper we consider a variant of the basic algorithm for the stochastic, multi-armed bandit problem that takes into account the empirical variance of the different arms. In earlier experimental works, such algorithms were found to outperform the competing algorithms. The purpose of this paper is to provide a theoretical explanation of these findings and provide theoretical guidelines for the tuning of the parameters of these algorithms. For this we analyze the expected regret and for the first time the concentration of the regret. The analysis of the expected regret shows that variance estimates can be especially advantageous when the payoffs of suboptimal arms have low variance. The risk analysis, rather unexpectedly, reveals that except for some very special bandit problems, the regret, for upper confidence bounds based algorithms with standard bias sequences, concentrates only at a polynomial rate. Hence, although these algorithms achieve logarithmic expected regret rates, they seem less attractive when the risk of suffering much worse than logarithmic regret is also taken into account.

Introduction and notations

In this paper we consider stochastic multi-armed bandit problems. The original motivation of bandit problems comes from the desire to optimize efficiency in clinical trials when the decision maker can choose between treatments but initially does not know which of the treatments is the most effective one [START_REF] Thompson | On the likelihood that one unknown probability exceeds another in view of the evidence of two samples[END_REF]. Multi-armed bandit problems became popular with the seminal paper of Robbins [START_REF] Robbins | Some aspects of the sequential design of experiments[END_REF], after which they have found applications in diverse fields, such as control, economics, statistics, or learning theory.

Formally, a K-armed bandit problem (K ≥ 2) is defined by K distributions, ν 1 , . . . , ν K , one for each "arm" of the bandit. Imagine a gambler playing with these K slot machines. The gambler can pull the arm of any of the machines. Successive plays of arm k yield a sequence of independent and identically distributed (i.i.d.) real-valued random variables X k,1 , X k,2 , . . . , coming from the distribution ν k . The random variable X k,t is the payoff (or reward) of the k-th arm when this arm is pulled the t-th time. Independence also holds for rewards across the different arms. The gambler facing the bandit problem wants to pull the arms so as to maximize his cumulative payoff.

The problem is made challenging by assuming that the payoff distributions are initially unknown. Thus the gambler must use exploratory actions in order to learn the utility of the individual arms, making his decisions based on the available past information. However, exploration has to be carefully controlled since excessive exploration may lead to unnecessary losses. Hence, efficient online algorithms must find the right balance between exploration and exploitation.

Since the gambler cannot use the distributions of the arms (which are not available to him) he must follow a policy, which is a mapping from the space of possible histories, ∪ t∈N + {1, . . . , K} t × R t , into the set {1, . . . , K}, which indexes the arms. Let µ k = E[X k,1 ] denote the expected reward of arm k. 4 By definition, an optimal arm is an arm having the largest expected reward. We will use k * to denote the index of such an arm. Let the optimal expected reward be µ * = max 1≤k≤K µ k .

Further, let T k (t) denote the number of times arm k is chosen by the policy during the first t plays and let I t denote the arm played at time t. The (cumulative) regret at time n is defined by

Rn n t=1 X k * ,t - n t=1 X It,TI t (t) .
Oftentimes, the goal is to minimize the expected (cumulative) regret of the policy, E[ Rn ]. Clearly, this is equivalent to maximizing the total expected reward achieved up to time n. It turns out that the expected regret satisfies

E[ Rn ] = K k=1 E[T k (n)]∆ k ,
where ∆ k µ * -µ k is the expected loss of playing arm k. Hence, an algorithm that aims at minimizing the expected regret should minimize the expected sampling times of suboptimal arms.

Early papers studied stochastic bandit problems under Bayesian assumptions (e.g., [START_REF] Gittins | Multi-armed Bandit Allocation Indices[END_REF]). Lai and Robbins [START_REF] Lai | Asymptotically efficient adaptive allocation rules[END_REF] studied bandit problems with parametric uncertainties. They introduced an algorithm that follows what is now called the "optimism in the face of uncertainty". Their algorithm computes upper confidence bounds for all the arms by maximizing the expected payoff when the parameters are varied within appropriate confidence sets derived for the parameters. Then the algorithm chooses the arm with the highest such bound. They show that the expected regret increases logarithmically only with the number of trials and prove that the regret is asymptotically the smallest possible up to a sublogarithmic factor for the considered family of distributions. Agrawal [START_REF] Szepesvári | Sample mean based index policies with O(log n) regret for the multiarmed bandit problem[END_REF] has shown how to construct such optimal policies starting from the sample-mean of the arms. More recently, Auer et al. [START_REF] Auer | Finite time analysis of the multiarmed bandit problem[END_REF] considered the case when the rewards come from a bounded support, say [0, b], but otherwise the reward distributions are unconstrained. They have studied several policies, most notably UCB1 which constructs the Upper Confidence Bounds (UCB) for arm k at time t by adding the bias factor

2b 2 log t T k (t -1)
to its sample-mean. They have proven that the expected regret of this algorithm satisfies

E[ Rn ] ≤ 8 k:µ k <µ * b 2 ∆ k log(n) + O(1). (1)
In the same paper they propose UCB1-NORMAL, that is designed to work with normally distributed rewards only. This algorithm estimates the variance of the arms and uses these estimates to refine the bias factor. They show that for this algorithm when the rewards are indeed normally distributed with means µ k and variances

σ 2 k , E[ Rn ] ≤ 8 k:µ k <µ * 32σ 2 k ∆ k + ∆ k log(n) + O(1). (2)
Note that one major difference of this result and the previous one is that the regret-bound for UCB1 scales with b 2 , while the regret bound for UCB1-NORMAL scales with the variances of the arms. First, let us note that it can be proven that the scaling behavior of the regret-bound with b is not a proof artifact: The expected regret indeed scales with Ω(b 2 ). Since b is typically just an a priori guess on the size of the interval containing the rewards, which might be overly conservative, it is desirable to lessen the dependence on it. Auer et al. introduced another algorithm, UCB1-Tuned, in the experimental section of their paper. This algorithm, similarly to UCB1-NORMAL uses the empirical estimates of the variance in the bias sequence. Although no theoretical guarantees were derived for UCB1-Tuned, this algorithm has been shown to outperform the other algorithms considered in the paper in essentially all the experiments. The superiority of this algorithm has been reconfirmed recently in the latest Pascal Challenge [START_REF] Auer | Exploration versus exploitation challenge[END_REF]. Intuitively, algorithms using variance estimates should work better than UCB1 when the variance of some suboptimal arms is much smaller than b 2 , since these arms will be less often drawn: suboptimal arms are more easily spotted by algorithms using variance estimates.

In this paper we study the regret of UCB-V, which is a generic UCB algorithm that use variance estimates in the bias sequence. In particular, the bias sequences of UCB-V take the form

2V k,T k (t-1) E T k (t-1),t T k (t -1) + c 3bE T k (t-1),t T k (t -1) ,
where V k,s is the empirical variance estimate for arm k based on s samples, E (viewed as a function of (s, t)) is a so-called exploration function for which a typical choice is E s,t = ζ log(t) (thus in this case, E independent of s). Here ζ, c > 0 are tuning parameters that can be used to control the behavior of the algorithm.

One major result of the paper (Corollary 1) is a bound on the expected regret that scales in an improved fashion with b. In particular, we show that for a particular settings of the parameters of the algorithm,

E[ Rn ] ≤ 10 k:µ k <µ * σ 2 k ∆ k + 2b log(n).
The main difference to the bound (1) is that b 2 is replaced by σ 2 k , though b still appears in the bound. This is indeed the major difference to the bound (2). 5In order to prove this result we will prove a novel tail bound on the sample average of i.i.d. random variables with bounded support that, unlike previous similar bounds, involves the empirical variance and which may be of independent interest (Theorem 1). Otherwise, the proof of the regret bound involves the analysis of the sampling times of suboptimal arms (Theorem 2), which contains significant advances compared with the one in [START_REF] Auer | Finite time analysis of the multiarmed bandit problem[END_REF]. This way we obtain results on the expected regret for a wide class of exploration functions (Theorem 3). For the "standard" logarithmic sequence we will give lower limits on the tuning parameters: If the tuning parameters are below these limits the loss goes up considerably (Theorems 4,5).

The second major contribution of the paper is the analysis of the risk that the studied upper confidence based policies have a regret much higher than its expected value. To our best knowledge no such analysis existed for this class of algorithms so far. In order to analyze this risk, we define the (cumulative) pseudo-regret at time n via

R n = K k=1 T k (n)∆ k .
Note that the expectation of the pseudo-regret and the regret are the same:

E[R n ] = E[ Rn ]
. The difference of the regret and the pseudo-regret comes from the randomness of the rewards. Sections 4 and 5 develop high probability bounds for the pseudo-regret . The same kind of formulae can be obtained for the cumulative regret (see Remark 2 p.13).

Interestingly, our analysis revealed some tradeoff that we did not expect: As it turns out, if one aims for logarithmic expected regret (or, more generally, for subpolynomial regret) then the regret does not necessarily concentrate exponentially fast around its mean (Theorem 7). In fact, this is the case when with positive probability the optimal arm yields a reward smaller than the expected reward of some suboptimal arm. Take for example two arms satisfying this condition and with µ 1 > µ 2 : the first arm is the optimal arm and ∆ 2 = µ 1 -µ 2 > 0. Then the distribution of the pseudo-regret at time n will have two modes, one at Ω(log n) and the other at Ω(∆ 2 n). The probability mass associated with this second mass will decay polynomially with n where the rate of decay depends on ∆ 2 . Above the second mode the distribution decays exponentially. By increasing the exploration rate the situation can be improved. Our risk tail bound (Theorem 6) makes this dependence explicit. Of course, increasing exploration rate increases the expected regret. This illustrates the tradeoff between the expected regret and the risk of achieving much worse than the expected regret. One lesson is thus that if in an application risk is important then it might be better to increase the exploration rate.

In Section 5, we study a variant of the algorithm obtained by E s,t = E s . In particular, we show that with an appropriate choice of E s = E s (β), for any 0 < β < 1, for an infinite number of plays, the algorithm achieves finite cumulative regret with probability 1 -β (Theorem 8). Hence, we name this variant PAC-UCB ("Probably approximately correct UCB"). Besides, for a finite timehorizon n, choosing β = 1/n then yields a logarithmic bound on the regret that fails with probability O(1/n) only. This should be compared with the bound O(1/ log(n) a ), a > 0 obtained for the standard choice E s,t = ζ log t in Corollary 2. Hence, we conjecture that knowing the time horizon might represent a significant advantage.

Due to limited space, some of the proofs are absent from this paper. All the proofs can be found in the extended version [START_REF] Audibert | Variance estimates and exploration function in multi-armed bandit[END_REF].

The UCB-V algorithm

For any k ∈ {1, . . . , K} and t ∈ N, let X k,t and V k,t be the empirical estimates of the mean payoff and variance of arm k:

X k,t 1 t t i=1 X k,i and V k,t 1 t t i=1 (X k,i -X k,t ) 2 ,
where by convention X k,0 0 and V k,0 0. We recall that an optimal arm is an arm having the best expected reward k * ∈ argmax k∈{1,...,K} µ k . We denote quantities related to the optimal arm by putting * in the upper index.

In the following, we assume that the rewards are bounded. Without loss of generality, we may assume that all the rewards are almost surely in [0, b], with b > 0. We summarize our assumptions on the reward sequence here:

Assumptions: Let K > 2, ν 1 , . . . , ν K distributions over reals with support [0, b]. For 1 ≤ k ≤ K, let {X k,t } ∼ ν k
be an i.i.d. sequence of random variables specifying the rewards for arm k. 6 Assume that the rewards of different arms are independent of each other, i.e., for any k, k ′ , 1 ≤ k < k ′ ≤ K, t ∈ N + , the collection of random variables, (X k,1 , . . . , X k,t ) and (X k ′ ,1 , . . . , X k ′ ,t ), are independent of each other.

The algorithm

Let c ≥ 0. Let E = (E s,t ) s≥0,t≥0 be nonnegative real numbers such that for any s ≥ 0, the function t → E s,t is nondecreasing. We shall call E (viewed as a function of (s, t)) the exploration function. For any arm k and any nonnegative integers s, t, introduce

B k,s,t X k,s + 2V k,s E s,t s + c 3bE s,t s (3)
with the convention 1/0 = +∞.

UCB-V policy:

At time t, play an arm maximizing B k,T k (t-1),t .

Let us roughly describe the behavior of the algorithm. At the beginning (i.e., for small t), every arm that has not been drawn is associated with an infinite bound which will become finite as soon as the arm is drawn. The more an arm k is drawn, the closer the bound (3) gets close to its first term, and thus, from the law of large numbers, to the expected reward µ k . So the procedure will hopefully tend to draw more often arms having greatest expected rewards.

Nevertheless, since the obtained rewards are stochastic it might happen that during the first draws the (unknown) optimal arm always gives low rewards. Fortunately, if the optimal arm has not been drawn too often (i.e., small T k * (t -1)), for appropriate choices of E (when E s,t increases without bounds in t for any fixed s), after a while the last term of (3) will start to dominate the two other terms and will also dominate the bound associated with the arms drawn very often. Thus the optimal arm will be drawn even if the empirical mean of the obtained rewards, X k * ,T k * (t-1) , is small. More generally, such choices of E lead to the exploration of arms with inferior empirical mean. This is why E is referred to as the exploration function. Naturally, a high-valued exploration function also leads to draw often suboptimal arms. Therefore the choice of E is crucial in order to explore possibly suboptimal arms while keeping exploiting (what looks like to be) the optimal arm.

The actual form of B k,s,t comes from the following novel tail bound on the sample average of i.i.d. random variables with bounded support that, unlike previous similar bounds (Bennett's and Bernstein's inequalities), involves the empirical variance.

Theorem 1. Let X 1 , . . . , X t be i.i.d. random variables taking their values in [0, b]. Let µ = E [X 1 ]
be their common expected value. Consider the empirical expectation X t and variance V t defined respectively by

X t = t i=1 X i t and V t = t i=1 (X i -X t ) 2 t .
Then for any t ∈ N and x > 0, with probability at least 1 -3e -x ,

|X t -µ| ≤ 2V t x t + 3bx t . (4)
Furthermore, introducing

β(x, t) = 3 inf 1<α≤3 log t log α ∧ t e -x/α , (5)
we have for any t ∈ N and x > 0, with probability at least 1 -β(x, t)

|X s -µ| ≤ 2V s x s + 3bx s (6)
hold simultaneously for s ∈ {1, 2, . . . , t}.

Remark 1. The uniformity in time is the only difference between the two assertions of the previous theorem. When we use ( 6), the values of x and t will be such that β(x, t) is of order of 3e -x , hence there will be no real price to pay for writing a version of (4) that is uniform in time. In particular, this means that if 1 ≤ S ≤ t is a random variable then (6) still holds with probability at least 1 -β(x, t) and when s is replaced with S.

Note that ( 4) is useless for t ≤ 3 since its r.h.s. is larger than b. For any arm k, time t and integer 1 ≤ s ≤ t we may apply Theorem 1 to the rewards X k,1 , . . . , X k,s , and obtain that with probability at least 1 -3 ∞ s=4 e -(c∧1)Es,t , we have µ k ≤ B k,s,t . Hence, by our previous remark at time t with high probability (for a high-valued exploration function E) the expected reward of arm k is upper bounded by B k,T k (t-1),t . The user of the generic UCB-V policy has two parameters to tune: the exploration function E and the positive real number c.

A cumbersome technical analysis (not reproduced here) shows that there are essentially two interesting types of exploration functions:

the ones in which E s,t depends only on t (see Sections 3 and4).

the ones in which E s,t depends only on s (see Section 5).

Bounds for the sampling times of suboptimal arms

The natural way of bounding the regret of UCB policies is to bound the number of times suboptimal arms are drawn (or the inferior sampling times). The bounds presented here significantly improve the ones used in [START_REF] Auer | Finite time analysis of the multiarmed bandit problem[END_REF]. This improvement is necessary to get tight bounds for the interesting case where the exploration function is logarithmic. The idea of the bounds is that the inferior sampling time of an arm can be bounded in terms of the number of times the UCB for the arm considered is over a some threshold value (τ in the statement below) and the number of times the UCB for an optimal arm is below the same threshold. Note that even though the above statements hold for any arm, they will be only useful for suboptimal arms. In particular, for a suboptimal arm the threshold can be chosen to lie between the payoff of an optimal arm and the payoff of the arm considered.

Theorem 2. Consider UCB-V. Then, after K plays, each arm has been pulled once. Further, the following holds: Let arm k and time n ∈ N + be fixed. For any τ ∈ R and any integer u > 1, we have

T k (n) ≤ u + n t=u+K-1 1 {∃s:u≤s≤t-1 s.t. B k,s,t >τ } +1 {∃s * :1≤s * ≤t-1 s.t. τ ≥B k * ,s * ,t } , (7)
hence

E [T k (n)] ≤ u + n t=u+K-1 t-1 s=u P B k,s,t > τ + n t=u+K-1 P ∃s : 1 ≤ s ≤ t -1 s.t. B k * ,s,t ≤ τ . (8)
Besides we have

P T k (n) > u ≤ n t=3 P B k,u,t > τ + P ∃s : 1 ≤ s ≤ n -u s.t. B k * ,s,u+s ≤ τ . (9)
Proof. The first assertion is trivial since at the beginning all arms has an infinite UCB, which becomes finite as soon as the arm has been played once. To obtain [START_REF] Lai | Machine learning and nonparametric bandit theory[END_REF], we note that

T k (n) -u ≤ n t=u+K-1 1 {It=k;T k (t)>u} = n t=u+K-1 Z k,t,u ,
where Taking the expectation on both sides of (7) and using the probability union bound, we obtain [START_REF] Robbins | Some aspects of the sequential design of experiments[END_REF]. Finally, (9) comes from a more direct argument that uses the fact that the exploration function ξ s,t is a nondecreasing function with respect to t. Consider an event such that the following statements hold:

Z k,t,u = 1 {It=k; u≤T k (t-1); 1≤T k * (t-1);B k,T k (t-1),t ≥B k * ,T k * (t-
∀t : 3 ≤ t ≤ n s.t. B k,u,t ≤ τ, ∀s : 1 ≤ s ≤ n -u s.t. B k * ,s,u+s > τ. . Then for any 1 ≤ s ≤ n -u and u + s ≤ t ≤ n, B k * ,s,t ≥ B k * ,s,u+s > τ ≥ B k,u,t .
This implies that arm k will not be pulled a (u + 1)-th time. Therefore we have proved by contradiction that

T k (n) > u ⊂ ∃t : 3 ≤ t ≤ n s.t. B k,u,t > τ ∪ ∃s : 1 ≤ s ≤ n -u s.t. B k * ,s,u+s ≤ τ , (10)
which by taking probabilities of both sides gives the announced result.

3 Expected regret of UCB-V

In this section, we consider that the exploration function does not depend on s (yet, E = (E t ) t≥0 is still nondecreasing with t). We will see that as far as the expected regret is concerned, a natural choice of E t is the logarithmic function and that c should not be taken too small if one does not want to suffer polynomial regret instead of logarithmic one. We derive bounds on the expected regret and conclude by specifying natural constraints on c and E t .

Theorem 3. We have

P(B k,s,t > µ * ) ≤ 2e -s∆ 2 k /(8σ 2 k +4b∆ k /3) , (11)
and

E[R n ] ≤ k:∆ k >0 1 + 8(c ∨ 1)E n σ 2 k ∆ 2 k + 2b ∆ k +ne -En 24σ 2 k ∆ 2 k + 4b ∆ k + n t=16En β (c ∧ 1)E t , t ∆ k , (12)
where we recall that β (c ∧ 1)E t , t is essentially of order e -(c∧1)Et (see [START_REF] Gittins | Multi-armed Bandit Allocation Indices[END_REF] and Remark 1).

Proof. Let E ′ n = (c ∨ 1)E n . We use [START_REF] Robbins | Some aspects of the sequential design of experiments[END_REF] with u being the smallest integer larger than 8

σ 2 k ∆ 2 k + 2b
∆ k E ′ n and τ = µ * . For any s ≥ u and t ≥ 2, we have

P(B k,s,t > µ * ) = P X k,s + 2V k,s Et s + 3bc E t s > µ k + ∆ k ≤ P X k,s + 2[σ 2 k +b∆ k /2]Et s + 3bc Et s > µ k + ∆ k + P V k,s ≥ σ 2 k + b∆ k /2 ≤ P X k,s -µ k > ∆ k /2 + P P s j=1 (X k,j -µ k ) 2 s -σ 2 k ≥ b∆ k /2 ≤ 2e -s∆ 2 k /(8σ 2 k +4b∆ k /3) , (13)
proving (11). Here in the last step we used Bernstein's inequality twice and in the second inequality we used that the choice of u guarantees that for any u ≤ s < t and t ≥ 2,

2[σ 2 k +b∆ k /2]Et s + 3bc Et s ≤ [2σ 2 k +b∆ k ]E ′ n u + 3b E ′ n u ≤ [2σ 2 k +b∆ k ]∆ 2 k 8[σ 2 k +2b∆ k ] + 3b∆ 2 k 8[σ 2 k +2b∆ k ] = ∆ k 2 2σ 2 k +b∆ k 2σ 2 k +4b∆ k + 3b∆ k 4σ 2 k +8b∆ k ≤ ∆ k 2 , (14)
since the last inequality is equivalent to (x -1) 2 ≥ 0 with x =

2σ 2 k +b∆ k 2σ 2 k +4b∆ k .
Summing up the probabilities in Equation ( 13) we obtain

t-1 s=u P(B k,s,t > µ * ) ≤ 2 ∞ s=u e -s∆ 2 k /(8σ 2 k +4b∆ k /3) = 2 e -u∆ 2 k /(8σ 2 k +4b∆ k /3) 1 -e -∆ 2 k /(8σ 2 k +4b∆ k /3) ≤ 24σ 2 k ∆ 2 k + 4b ∆ k e -u∆ 2 k /(8σ 2 k +4b∆ k /3) ≤ 24σ 2 k ∆ 2 k + 4b ∆ k e -E ′ n , (15)
where we have used that 1 -e -x ≥ 2x/3 for 0 ≤ x ≤ 3/4. By using ( 6) of Theorem 1 to bound the other probability in ( 8), we obtain that

E [T k (n)] ≤ 1 + 8E ′ n σ 2 k ∆ 2 k + 2b ∆ k + ne -E ′ n 24σ 2 k ∆ 2 k + 4b ∆ k + n t=u+1 β((c ∧ 1)E t , t),
which by u ≥ 16E n gives the announced result.

In order to balance the terms in ( 12) the exploration function should be chosen to be proportional to log t. For this choice, the following corollary gives an explicit bound on the expected regret:

Corollary 1. If c = 1 and E t = ζ log t for ζ > 1, then there exists a constant c ζ depending only on ζ such that for n ≥ 2 E[R n ] ≤ c ζ k:∆ k >0 σ 2 k ∆ k + 2b log n. ( 16
)
For instance, for ζ = 1.2, the result holds for c ζ = 10.

Proof (Sketch of the proof ). The first part, (16), follows directly from Theorem 3. Let us thus turn to the numerical result. For n ≥ K, we have R n ≤ b(n -1) (since in the first K rounds, the optimal arm is chosen at least once). As a consequence, the numerical bound is nontrivial only for 20 log n < n -1, so we only need to check the result for n > 91. For n > 91, we bound the constant term using 1 ≤ log n log 91 ≤ a 1 2b ∆ k (log n), with a 1 = 1/(2 log 91) ≈ 0.11. The second term between the brackets in (12) is bounded by a 2

σ 2 k ∆ 2 k + 2b
∆ k log n, with a 2 = 8×1.2 = 9.6. For the third term, we use that for n > 91, we have 24n -0.2 < a 3 log n, with a 3 = 24 91 0.2 ×log 91 ≈ 0.21. By tedious computations, the fourth term can be bounded by a 4 2b ∆ k (log n), with a 4 ≈ 0.07. This gives the desired result since a 1 + a 2 + a 3 + a 4 ≤ 10.

As promised, Corollary 1 gives a logarithmic bound on the expected regret that has a linear dependence on the range of the reward, contrary to bounds for algorithms that do not take into account the empirical variance of the rewards (see e.g. the bound (1) that holds for UCB1).

The previous corollary is well completed by the following result, which essentially says that we should not use

E t = ζ log t with ζ < 1.
Theorem 4. Consider E t = ζ log t and let n denote the total number of draws. Whatever c is, if ζ < 1, then there exist some reward distributions (depending on n) such that the expected number of draws of suboptimal arms using the UCB-V algorithm is polynomial in the total number of draws the UCB-V algorithm suffers a polynomial loss.

So far we have seen that for c = 1 and ζ > 1 we obtain a logarithmic regret, and that the constant ζ should not be taken below 1 (whatever c is) without risking to suffer polynomial regret. Now we consider the last term in B k,s,t , which is linear in the ratio E t /s, and show that this term is also necessary to obtain a logarithmic regret, since we have:

Theorem 5. Consider E t = ζ log t. Whatever ζ is, if cζ < 1/6,
there exist probability distributions of the rewards such that the UCB-V algorithm suffers a polynomial loss.

To conclude the above analysis, natural values for the constants appearing in the bound are the following ones

B k,s,t X k,s + 2V k,s log t s + b log t 2s .
This choice corresponds to the critical exploration function E t = log t and to c = 1/6, that is, the minimal associated value of c in view of the previous theorem. In practice, it would be unwise (or risk seeking) to use smaller constants in front of the last two terms.

Concentration of the regret

In real life, people are not only interested in the expected rewards that they can obtain by some policy. They also want to estimate probabilities of obtaining much less rewards than expected, hence they are interested in the concentration of the regret. This section starts with the study of the concentration of the pseudo-regret, since, as we will see in Remark 2 p.13, the concentration properties of the regret follow from the concentration properties of the pseudo-regret. We still assume that the exploration function does not depend on s and that E = (E t ) t≥0 is nondecreasing. Introduce βn (t) 3 min

α≥1 M∈N s0=0<s1<•••<sM =n s.t. sj+1≤α(sj +1) M-1 j=0 e - (c∧1)E s j +t+1 α . ( 17
)
We have seen in the previous section that in order to obtain logarithmic expected regret, it is natural to take a logarithmic exploration function. In this case, and also when the exploration function goes to infinity faster than the logarithmic function, the complicated sum in (17), up to second order logarithmic terms, is of the order e -(c∧1)Et . This can be seen by considering (disregarding rounding issues) the geometric grid s j = α j with α close to 1. The next theorem provides a bound for the tails of the pseudo-regret.

Theorem 6. Let v k 8(c ∨ 1) σ 2 k ∆ 2 k + 4b 3∆ k , r 0
k:∆ k >0 ∆ k 1 + v k E n .
Then, for any x ≥ 1, we have

P R n > r 0 x ≤ k:∆ k >0 2ne -(c∨1)Enx + βn (⌊v k E n x⌋) , (18)
where we recall that βn (t) is essentially of order e -(c∧1)Et (see the above discussion). 7

Proof (sketch of the proof ). First note that

P R n > r 0 x = P k:∆ k >0 ∆ k T k (n) > k:∆ k >0 ∆ k (1 + v k E n )x ≤ k:∆ k >0 P T k (n) > (1 + v k E n )x .
Let E ′ n = (c∨1)E n . We use [START_REF] Thompson | On the likelihood that one unknown probability exceeds another in view of the evidence of two samples[END_REF] with τ = µ * and u = ⌊(1

+ v k E n )x⌋ ≥ v k E n x. From (11) of Theorem 3 , we have P(B k,u,t > µ * ) ≤ 2e -u∆ 2 k /(8σ 2 k +4b∆ k /3) ≤ 2e -E ′ n x .
To bound the other probability in (9), we use α ≥ 1 and the grid s 0 , . . . , s M realizing the minimum of (17) when t = u. Let I j = {s j + 1, . . . , s j+1 }. Then where the second to last inequality comes from an appropriate union bound argument (see [START_REF] Audibert | Variance estimates and exploration function in multi-armed bandit[END_REF] for details).

When E n ≥ log n, the last term is the leading term. In particular, when c = 1 and E t = ζ log t with ζ > 1, Theorem 6 leads to the following corollary, which essentially says that for any z > γ log n with γ large enough,

P R n > z ≤ C z -ζ ,
for some constant C > 0: 7 Here ⌊x⌋ denotes the largest integer smaller or equal to x.

Corollary 2. When c = 1 and E t = ζ log t with ζ > 1, there exist κ 1 > 0 and κ 2 > 0 depending only on b, K, (σ k ) k∈{1,...,K} , (∆ k ) k∈{1,...,K} satisfying that for any ε > 0 there exists Γ ε > 0 (tending to infinity when ε goes to 0) such that for any n ≥ 2 and any z > κ 1 log n

P R n > z ≤ κ 2 Γ ε log z z ζ(1-ε)
Since the regret is expected to be of order log n the condition z = Ω(log n) is not an essential restriction. Further, the regret concentration, although increasing with ζ, is pretty slow. For comparison, remember that a zero-mean martingale M n with increments bounded by 1 would satisfy P(M n > z) ≤ exp(-2z 2 /n).

The slow concentration for UCB-V happens because the first Ω(log(t)) choices of the optimal arm can be unlucky, in which case the optimal arm will not be selected any more during the first t steps. Hence, the distribution of the regret will be of a mixture form with a mode whose position scales linearly with time and which decays only at a polynomial rate, which is controlled by ζ. 8 This reasoning relies crucially on that the choices of the optimal arm can be unlucky. Hence, we have the following result:

Theorem 7. Consider E t = ζ log t with cζ > 1.
Let k denote the second optimal arm. If the essential infimum of the optimal arm is strictly larger than µ k, then the pseudo-regret has exponentially small tails. Inversely, if the essential infimum of the optimal arm is strictly smaller than µ k , then the pseudo-regret has only polynomial tail.

Remark 2. In Theorem 6 and Corollary 2, we have considered the pseudo-regret:

R n = K k=1 T k (n)∆ k instead of the regret Rn n t=1 X k * ,t - n t=1 X It,TI t (t)
. Our main motivation for this was to provide as simple as possible formulae and assumptions. The following computations explains that when the optimal arm is unique, one can obtain similar contration bounds for the regret. Consider the interesting case when c = 1 and E t = ζ log t with ζ > 1. By modifying the analysis slightly in Corollary 2, one can get that there exists κ 1 > 0 such that for any z > κ 1 log n, with probability at least 1 -z -1 , the number of draws of suboptimal arms is bounded by C z for some C > 0. This means that the algorithm draws an optimal arm at least n -C z times. Now if the optimal arm is unique, this means that n -Cz terms cancel out in the summations of the definition of the regret. For the Cz terms which remain, one can use standard Bernstein inequalities and union bounds to prove that with probability 1-Cz -1 , we have Rn ≤ R n + C ′ √ z. Since the bound on the pseudo-regret is of order z (Corollary 2), a similar bound holds for the regret.

an UCB algorithm which has nice properties with high probability (Probably Approximately Correct), hence the name of it. Note that in this setting, the quantity B k,s,t does not depend on the time t so we will simply write it B k,s . Besides, in order to simplify the discussion, we take c = 1. Theorem 8. Let β ∈ (0, 1). Consider a sequence (E s ) s≥0 satisfying E s ≥ 2 and 4K s≥7 e -Es ≤ β.

(

) 19
Consider u k the smallest integer such that

u k Eu k > 8σ 2 k ∆ 2 k + 26b 3∆ k . ( 20
)
With probability at least 1 -β, the PAC-UCB policy plays any suboptimal arm k at most u k times.

Let q > 1 be a fixed parameter. A typical choice for E s is

E s = log(Ks q β -1 ) ∨ 2, ( 21
)
up to some additive constant ensuring that (19) holds. For this choice, Theorem 8 implies that for some positive constant κ, with probability at least 1 -β, for any suboptimal arm k (i.e., ∆ k > 0), its number of play is bounded by

T k,β κ σ 2 k ∆ 2 k + 1 ∆ k log K σ 2 k ∆ 2 k + b ∆ k β -1 ,
which is independent of the total number of plays! This directly leads to the following upper bound on the regret of the policy at time n

K k=1 T k (n)∆ k ≤ k:∆ k >0 T k,β ∆ k . (22)
One should notice that the previous bound holds with probability at least 1 -β and on the complement set no small upper bound is possible: one can find a situation in which with probability of order β, the regret is of order n (even if (22) holds with probability greater than 1-β). More formally, this means that the following bound cannot be essentially improved (unless additional assumptions are imposed):

E[R n ] = K k=1 E[T k (n)]∆ k ≤ (1 -β) k:∆ k >0 T k,β ∆ k + βn
As a consequence, if one is interested in having a bound on the expected regret at some fixed time n, one should take β of order 1/n (up to a logarithmic factor): (23)

Open problem

When the horizon time n is known, one may want to choose the exploration function E depending on the value of n. For instance, in view of Theorems 3 and 6, one may want to take c = 1 and a constant exploration function E ≡ 3 log n. This choice ensures logarithmic expected regret and a nice concentration property:

P R n > 24 k:∆ k >0 σ 2 k ∆ k + 2b log n ≤ C n . (24)
This algorithm does not behave as the one which simply takes E s,t = 3 log t. Indeed the algorithm with constant exploration function E s,t = 3 log n concentrates its exploration phase at the beginning of the plays, and then switches to exploitation mode. On the contrary, the algorithm which adapts to the time horizon explores and exploits during all the time interval [0; n]. However, in view of Theorem 7, it satisfies only

P R n > 24 k:∆ k >0 σ 2 k ∆ k + 2b log n ≤ C (log n) C .
which is significantly worse than ( 24). The open question is: is there an algorithm that adapts to time horizon which has a logarithmic expected regret and a concentration property similar to (24)? We conjecture that the answer is no.

P 1 j=0P- 1 j=0P

 11 ∃s : 1 ≤ s ≤ n -u s.t. B k * ,s,u+s ≤ µ * ≤ M-∃s ∈ I j s.t. B k * ,s,sj +u+1 ≤ µ * ≤ M∃s ∈ I j s.t. s(X k * ,s -µ * ) + 2sV k * ,s E sj +u+1 + 3bcE sj +u+1 ≤ 0 E s j +u+1 α = βn (u) ≤ βn (⌊v k E n x⌋),

Theorem 9 . 2 k

 92 Let n ≥ 7 be fixed. Consider the sequence E s = log[Kn(s + 1)]. For this sequence, the PAC-UCB policy satisfies with probability at least 1 -4 log(n/7) n , for any k : ∆ k > 0, the number of plays of arm k up to time n is bounded by 1 + k log(Kn 2 ). -the expected regret at time n satisfies E[R n ] ≤ k:∆ k >0 24σ ∆ k + 30b log(n/3).

N denotes the set of natural numbers, including zero and N + denotes the set of strictly positive integers.

Although this is unfortunate, it is possible to show that the dependence on b is unavoidable.

The i.i.d. assumption can be relaxed, see e.g.,[START_REF] Lai | Machine learning and nonparametric bandit theory[END_REF].

PAC-UCBIn this section, we consider that the exploration function does not depend on t: E s,t = E s . We show that for an appropriate sequence (E s ) s≥0 , this leads to[START_REF] Robbins | Some aspects of the sequential design of experiments[END_REF] Note that entirely analogous results hold for UCB1.

Acknowledgements. Csaba Szepesvári greatly acknowledges the support received through the Alberta Ingenuity Center for Machine Learning (AICML) and the Computer and Automation Research Institute of the Hungarian Academy of Sciences, and the PASCAL pump priming project "Sequential Forecasting". The authors thank Yizao Wang for the careful reading of an earlier version of this paper.


president Michel Cosnard

chairman Jean-François Chenot

Jean-Yves Le Reste

M Me

Anne-Marie Lehr-Drylewicz

M Emmanuel Lagarde

M Remy Brajeul

M Jacques-Olivier

Pers

In the name of HCERES, 1

 Introduction History and geographical location of the unit

The unit is located in Brest, as part of the Université de Bretagne Occidentale (UBO), and hosted at the Brest Regional University Hospital (CHRU).

The department of general practice ("Département Universitaire de Médecine Générale" -DUMG) was founded in 1990 and was initially only active in teaching. In 2005, the department started research in primary care in close collaboration with the European General Practice Research Network (EGPRN). This has created an increased demand for supervision of professional theses ("thèses professionnelles"). Since 2012, the department is responsible of 300 residents and a network of 208 clinical teachers (representing 25% of all General Practitioners GPs in the area), with 69 involved in research activities.

In April 2014, the DUMG was merged with the Department of Public Health and the Cancer Registry to form the new unit SPURBO. The cancer registry is specialized in gastrointestinal tumours and was created in 1984. The register is part of FRANCIM ("France incidence mortalité") network. In 2012, it was successfully audited by the CNIL ("Commission nationale de l'informatique et des libertés"). The register cooperates with ADEC ("Association de dépistage de cancers dans le Finistère").

The section of Public Health is specialized in addiction medicine and infectious disease. This has added epidemiological expertise to the unit. This combination of Public Health and Primary Care / General Practice has some models in France and elsewhere, e.g. the Netherlands institute for health services research (NIVEL).

At the time of the report the unit has been in place for less than two years.

Management team

Mr Jean-Yves LE RESTE is the head of the unit.

HCERES nomenclature

SVE6

Scientific domains

Unlike in the Northern European countries, the UK, Canada, the United States of America and Australia, research in Primary Care / General Practice in France has been neglected for a long time. Therefore, research skills and academic staff able to do research in this field is still in an early developmental stage, either at local or national level, with few exception. However, primary care research in France has made a great leap forward in the past 10 years.

Preventive medicine at the population level of common health problems is in the focus of past and planned research projects of the unit. The main scientific objective is to develop models to describe disease pattern and identify underserved and excluded patients groups. The ultimate goal is to design intervention studies based on these models to address these issues. The approaches are both quantitative and qualitative. The section of General Practice has developed methodological expertise in qualitative research and in the conduct of consensus processes.

Global assessment of the unit

The group in General Practice ("soins primaires") succeeded in shifting from exclusive educational activities to first steps in research over the past years. The unit managed to organize a network of local General Practitioners and to get them involved in research. This is additionally supported by the help of residents in primary care (étudiants en médecine du troisième cycle) supervised by the department contributing to patient recruitment. The close network of practices involved in teaching activities was a key element for this development. This allowed access to data and to recruit physicians interested in pursuing a part-time research activity. The members of the unit strongly benefited from their active collaboration with EGPRN (European General Practice Research Network). Although there is a noticeable gap between the publication output and the ongoing projects, this has resulted in successful national and international collaboration and eventually publications together with a first success in a national research grant application. A particular strength of the group is qualitative research. They have conducted several pilot studies on subjects relevant to General Practice that have the potential to lead to further funded research projects. Currently, there are three PhD students who are co-supervised by the University of Antwerp and one thesis was recently successfully defended. This small number of PhD students is partly related to structural problems obtaining thesis supervision for qualitative research in General Practice, since the field does not benefit from a well-established tradition in France unlike in Belgium and most Northern European countries. External thesis supervision allows transfer of research knowledge from foreign research team with higher skill and expertise in the domain.

The group in Public Health includes only two members but appears to be very productive. One major field of research activities is addiction medicine, another is infectious diseases. The publication output is excellent. They are collaborative research projects with the group in General Practice that resulted in joint presentations at conferences. The group on Cancer Registry has two researchers and one administrative staff. The research is focused on gastrointestinal disorders. The publication output is high but it is noticeable that the senior scientist of the group is neither listed as a lead nor as a leading author in any paper published in the past 5 years. Common research projects with the group in General Practice are ongoing but did not result so far in joint presentations.

From the international point of view it seems noticeable that none of the staff of all three groups is working full time in research. All researchers have substantial clinical duties and teaching duties, which are not addressed and evaluated in this report.

Strengths and opportunities in the context

The potential added value of the merger of the three groups includes the exchange of research skills, improved data access and collaborative research projects.

The unit has managed to create a considerable research network of practices involved in research activities, recruited from their teaching network and covering the entire region. As a consequence, a large proportion of residents in General Practice (50%) decided to prepare their professional theses under the supervision of the unit. Those residents are strongly involved in research projects and very helpful for large and rapid patient recruitment. This is a considerable strength, making the unit attractive as research partner for other clinical specialties, and is an opportunity to expand collaboration with local and international partners. This is also the basis for ongoing and anticipated collaboration with addiction medicine and cancer prevention. The Cancer Registry is well connected at national level, as demonstrated by the high number of publications to which the senior scientists contributed.

Weaknesses and threats in the context

A common research strategy for all three groups of the unit is visible but needs to be refined. The projects presented and anticipated cover a large area but lack a profile building internal coherence. Although there is support from the hospital clinical research unit (DRCI), there is a lack of internal epidemiological and biostatistical research expertise. The committee has been, however, informed of the planned employment of an epidemiologist in the near future.

Among the publications from the group in General Practice there are few original research articles. Two of the articles evolve around consensus of definitions (multimorbidity) or translations and only few research articles with clinical data. Among the listed 5 most important publications, two are only research protocols, not original research, of so far unpublished research projects.

Despite the statement that systematic reviews according to international standards (PRISMA, AMSTAR) are part of the research strategy, only one systematic review has been published and another one presented at a conference. A better systematic literature search and publications of systematic, or even narrative, reviews in the area might help focusing the research profile and strategy. The next step, moving from models based on qualitative research to quantitative epidemiological and intervention studies, has a broad scope. The group will need the support and the experience of other units and of the clinical research unit (DRCI).

The publication list from the Cancer Registry group does not list any group members as first or senior authors, indicating that they mainly provided data. The registry is limited to gastrointestinal cancers, which reduces the scope for joint research projects and international collaborations. Ways to expand the registry to all cancers should be pursued actively.

Recommendations

The unit should come up with a description of its common mission.

The unit research topic should be more precise than the vast field of preventive medicine. A more focused common research topic would enhance the profile of the unit, and allow excellence and leadership in the research field.

To identify research areas where the unit could contribute to science, beyond being the first in France addressing a research question, more systematic reviews should be conducted.

The supervision of professional theses should lead to more numerous published articles and help increasing the production of systematic reviews.

The unit should strive for more visibility.

The group in General Practice should continue its involvement with EGPRN, but should widen its scope and gain experience with more competitive organisations like the Nordic Federation of General Practice, the Society for Academic Primary Care (SAPC) and the North American Primary Care Research Group (NAPCRG). Additionally, the group should initiate research in primary care relevant to specialists and target specialized congresses and journals. A start could be national and international meeting in addiction medicine.

The projects should become more clinically relevant for the GPs in the network that are providing access to data and patients for research projects.

The group in General Practice should continue doing qualitative research and provide expertise to the rest of the unit. However, the unit needs to develop and share more skills in quantitative research.

The unit should increase its involvement in the international scientific community. The HDR qualified researchers should supervise PhD students, and the 5-year plan should include the defence of PhD theses and HDR.

More involvement of researchers in master programs, or even the creation of a master program, in research in primary care would be an asset.

N7

  Permanent researchers from Institutions and similar positions N3: Other permanent staff (technicians and administrative personnel) N4: Other professors (Emeritus Professor, on-contract Professor, etc.) N5: Other researchers from Institutions (Emeritus Research Director, Postdoctoral students, visitors, etc.) N6: Other contractual staff (technicians and administrative personnel) 2 spent at least 12 months in the unit Number of Research Supervisor Qualifications (HDR) obtained during the period *at the University of Antwerp 2  Overall assessment of the unit Introduction SPURBO is an emergent unit that exists for less than 2 years and wishes to become a permanent research unit. It is composed of three groups, General Practice, Public Health and the Cancer Registry of Finistère, which have merged in April 2014.

  Additional favourable factors are the strong connections with many European and Non-European university departments. Applications to European funds are in preparation (Horizon 2020) with European partners. The section of General Practice has developed good experience in qualitative research methods, and has support for quantitative research from the hospital's clinical research unit ("Direction de Recherche Clinique et Innovation" -DRCI).

5) 2 The evaluation reports "are signed by the chairman of the expert committee". expert committee, the composition of which is specified below.

The assessments contained herein are the expression of an independent and collegial reviewing by the committee.


president Michel Cosnard

Evaluation report

This report is the sole result of evaluation by the expert committee, the composition of which is specified below. The assessments contained herein are the expression of an independent and collegial reviewing by the committee.

Unit name:

Pathophysiology The unit started in 2008 under the direction of Mr Olivier BOYER. The research unit, evaluated in 2010 and renewed in 2012, is composed of 2 teams. For the next contract, some members of team 1 will join team 2, whereas members from the unit "Micro-Environnement et Renouvellement Cellulaire Intégré" (UPRES EA 3829) from Rouen will join team 1 at the end of 2016. Both teams carry out their research within the Faculty of Medicine and Pharmacy. The research unit is in charge of IRIB, the Institute of Research and Innovation in Biomedecine headed by Mr Olivier BOYER, which includes several platforms and is used by 21 Inserm, CNRS, University and hospital structures. Six engineers from the research unit are affiliated to IRIB.

Management team

For the 2017-2021 period, the research unit will be headed by Mr Olivier BOYER.

HCERES nomenclature

SVE1_LS3, SVE1_LS4, SVE1_LS6

Scientific domains

The main areas of research are related to the regulation of immune response in neuromuscular diseases, autoimmune dermatological disorders and drug-induced toxidermia. In parallel, several translational projects concern the identification and characterization of diagnostic biomarkers in rheumatoid arthritis, analysis of therapy efficacy and future projects will deal with regenerative cell/tissue therapy. The unit is composed of two teams and each team develops three main domains of research. These research topics are under the responsibility of 6 principal investigators (3 PU-PH, 1 MCU, 1 research engineer (IR) and 1 postdoc.).

Unit workforce

Unit

Both fundamental and clinical researches are developed. The main axes are i) studies on the physiological and pathophysiological mechanisms regulating autoimmunity in myopathies and the development of clinical trials in acquired muscle disease; ii) studies on the pathophysiological mechanisms of rhumatoid arthritis, autoimmune skin diseases and drug allergy. Both teams develop murine models.

Global assessment of the unit

The unit has a high expertise in its field of research and maintains an excellent research in association with the patient cohorts available The two teams are well recognized in their specific domains. Team 1 addresses questions in three domains: immunoregulatory approaches using experimental mouse models, role of neuropeptides VIP and PACAP in both anti-inflammation and neuroprotection and pathophysiology of myositis. Team 2 carries out a superb translational research in the field of autoimmune diseases, with a focus on dermatoses. Unit members participate in events for public and patient information. Most scientists of the unit are heavily involved in teaching in medical, pharmaceutical and scientific masters or doctoral schools.

Strengths and opportunities in the context

The main strengths include the translational research, the available cohorts of patients and the contribution to numerous clinical boards.

The strong involvement in teaching favours the recruitment of young scientific and medical investigators and improves the visibility of the unit.

The director is extremely active in unifying and energizing research in Rouen and in the Normandy region. The IRIB platform is one example of his efficiency in this domain.

Team leaders show a very good mentoring record together with engineers highly involved in training of PhD and Master students.

A major strength of team 2 is its composition including both highly recognized clinicians and experienced engineers. The access to well-characterized patient cohorts and to various cutting-edge experimental methods and animal models is an asset. A further competitive advantage of team 2 and its project is their extensive, projectrelevant and internationally leading expertise in molecular immunology and their cooperation with national (Pasteur Institute) and international (Singapore Network) laboratories.

Weaknesses and threats in the context

There are too many objectives with regard to the number of researchers and their availability.

While at this stage no obvious major shortcomings are apparent, a possible aspect to consider is the limited time that PIs and other team members with heavy clinical duties can devote to each project.

A first long-standing shortcoming is the absence of permanent academic researchers.

The unit should attract full-time permanent researchers (through institutional mobility) or de novo recruitment.

The position of a group leader, who arrived in 2014 in team 1, is not secured (post-doctoral position) and further hampers long-term projects.

Finally, while the teams successfully secured financial support in the past, the situation will be more difficult in the future, except for some translational projects.

Recommendations

The unit should refocus the projects.

An effort to promote "emergent" or independent teams with clearly identified leaders and work forces should be considered.

There is a need to strengthen the complementarities and synergies between teams and their members.

  ANd Innovative THERapeutic approaches in autoreactive diseases

	Unit acronym:	PANTHER
	Label requested:	UMR INSERM -University of Rouen
	Current number:	U905
	Name of Director (2015-2016):	Mr Olivier BOYER
	Name of Project Leader (2017-2021):	Mr Olivier BOYER
	Expert committee members
		Ms Sophie EZINE
	Representative(s) of supervising institutions and bodies:
		Ms Christine GUILLARD, Chargée de mission, Inserm
		Mr Samir OULDALI, Délégué Regional, Inserm
		Mr Cafer ÖZKUL, Université de Rouen
		Mr Laurent YON, Université de Rouen

Chair:

Mr Jose BOUCRAUT, UMR CNRS 7286, Aix-Marseille Université, Marseille (representative of the CNU) Experts: Ms Yolande RICHARD, Inserm U1016, Paris (representative of the Inserm) Mr Cassian SITARU, University of Freiburg, Germany Scientific delegate representing the HCERES: Head of Doctoral School: Mr Patrice LEROUGE, Doctoral school ED NBISE n° 497, "Normandy's Integrative Biology, Health, Environment".


Mr Olivier Boyer

LIBLAU Mr Roland

Ms Dominique Kaiserlian

Ms Valérie Zimmermann

Bertrand Mr

Dubois

Paul Mr

Hofman

Ms Christine Tuffereau

Mr Cafer Ozkul

Directeur Olivier Boyer

The site visit of the Rouen Inserm U905 took place on December 2 nd , 2010. The evaluating committee evaluated the 2 teams together, but were divided in 2 groups to discuss with either students or technical staff. Committee members collaborated closely to prepare the final report.

The committee had sufficient time to listen to presentations, assess the research of the teams, assess the environment for the PhD students and technical staff as well as having the needed discussions afterwards. At the end of the 2 teams' presentations, an in-depth discussion among panel members took place to summarize salient issues, exchange views and organize the preparation of the final report.

• History and geographical localization of the research unit, and brief presentation of its field and scientific activities

The Inserm unit 905 (Physiopathology and Biotherapy of inflammatory and autoimmune diseases: Director Olivier BOYER) started in 2008, and continued the research efforts of the former Inserm Unit 519 ("Defense proteins involved in inflammatory immune responses") headed by François TRON at the University Hospital Centre in Rouen. Originally, the three fields of research of U519 were: (1) hepatic proteins in the systemic inflammatory response syndrome;

(2) complement and tissue physiopathology; and (3) auto-antibodies in specific and nonspecific autoimmune organ disease with emphasis on hepatomas, cancer, disorders of the central nervous system and autoimmune diseases, such as pemphigus, lupus and rheumatoid arthritis.

Initially created as an Avenir team (Fundamental immuno-myology and biotherapy), integrated into the IFR 23, U905 has expanded its manpower and scientific goals and built on the scientific and clinical "history" of the previous Unit. Presently, U905 consists of 45 persons divided into two teams. It is affiliated to the Inserm ITMO "Immunology-hematology-pneumology" (IHP) that encompasses the field of biotherapies.

The overall objectives of U905 relate to basic research studying the molecular mechanisms that underlie the regulation of normal and pathological immune responses as well as translational research that includes clinical studies in the field of inflammatory and autoimmune diseases of the locomotor apparatus and the skin. The latter project is one of the strategic axes of the Teaching Hospital Institute of Biomedical Research (IHURBM) at the site of Martainville.

Team 1

" Physiopathology and biotherapies of immune pathologies of locomotor apparatus" includes the group of rheumatologists of the Unit and is headed by Olivier BOYER and Michel SEMAN. Their main research efforts focus on (i) the identification of novel physiological and physiopathological mechanisms of autoimmune regulation in myositis by developing and studying experimental mouse models of auto-immune myositis, as well as on (ii) the biology of regulatory T cells and in particular the immunoregulatory role of ectonucleotides. Furthermore, the team conducts clinical studies in the field of myositis and rheumatoid arthritis. Their work has led to the development of a novel transgenic mouse model that is used to study the molecular mechanisms of tolerance towards muscle-expressed autoantigens, to the demonstration of the role of ectonucleotides in the homeostasis of regulatory T cells, to the identification of prognostic and drug-responsiveness biomarkers in rheumatoid arthritis, as well as novel diagnostic tools in inflammatory myopathies. Overall, the Unit makes extensive use of current technologic approaches, such as transcriptome and proteome analysis, and carries out innovative diagnostic and theranostic research, which is guided by the results from cellular and genetic therapies.

• Staff members (on the basis of the application file submitted to the AERES) 2  Overall appreciation on the research unit

• Summary

The research unit 'Pathophysiology and biotherapy of inflammatory and autoimmune diseases' studies the immune response and its regulation in health and autoimmunity, in particular in autoimmune and inflammatory disorders affecting muscle, joint and skin. In addition to the increase in the understanding of these pathologies, research aims at improving diagnosis and therapy. The unit comprises two teams: (1) the BOYER team that focuses on muscle and joint; and (2) the MUSETTE team the research of which is centered on skin. The teams are building on high risk/high gain projects. This has worked very well and has led to highly original results and novel concepts. The teams are primarily committed to clinical questions and therefore the impact of their work is beyond doubt. Appreciations of each team are given in the section 4.

Science, management, as well as the social and scientific atmosphere, are very good, which, by and large, is the result of the enthusiasm and commitment of the director. The long-term vision of the unit is to excel in basic and translational research with respect to autoimmunity or chronic inflammatory diseases affecting the three above-mentioned organs. The committee members consider this an important goal for which there is a clear and non-occupied niche at the national as well as international level. The proposed reorganization of the unit for the next five-year period, i.e., focus of the BOYER team on muscle and focus of the MUSETTE team on both joint and skin, is anticipated to represent a better strategy to reach this goal. Teams will be betterfocused and balanced with respect to size and resources. In the future, the dynamics of this unit, good level of publications, space availability and strong support by the university should allow attraction of new additional high profile investigators.

The research unit is well embedded in the infrastructure of the University of Rouen and takes advantage of the excellent organization of the IFR in different facilities with the mutualization of human resources. The output of the unit is graded as very good with recent publications in J Exp Med and Sci Transl Med. Also the valorization is graded as very good, with patents with respect to a diagnostic gene set and a quantitative assay for autoantibodies for myositis, as well as gene sets predicting responses towards anti-inflammatory drugs in the setting of arthritis. Provided the recent upward momentum is maintained, it is anticipated that the international recognition of this research unit will further increase. One minor point of caution is a tendency to over-emphasize the value of preclinical models that do not, in all cases, have proven clinical relevance. The committee feels that the research unit is well on its way to become a center of excellence, and that it may benefit from one or several full-time researcher(s) with a permanent position at an associate professor level to reinforce the existing teams and contribute to the clinical validation of the results obtained in their mouse models or to lead to the emergence of a third team (i.e., each team covers the studies on a single organ).

• Strenghts and opportunities

The Unit performs excellent translational research in autoimmune processes affecting the muscle, the skin and joints. There is no doubt, when considering their past and present achievements, that they conduct very good basic and clinical research and that they are clearly undertaking projects of excellence in the three fields. This is also highlighted by recent major publications in top international journals, strong patents as well as by strong financial support from both institutional and industrial partners.

The research strength of the unit is supported by the clinical origin of the 2 team leaders, their involvement in pathophysiological research via commitment and skills to develop relevant physiopathological animal models reproducing human diseases (Team 1, O. BOYER). The presence of many clinicians with robust knowledge of human immunology and the commitment to physiopathological and clinical research are emphasized by the originality and pertinence of the projects for the diagnosis and treatment of autoimmune diseases.

Both teams benefit from access to large and well-diagnosed patient cohorts, both through local hospital departments and via international collaborations and have good access to technology platforms in the IFR.

The unit has many preclinical models in place, and the projects of both teams are well defined and fill a niche in French and outside French research.

Both teams provide good mentoring of PhD students.

• Weaknesses and threats

The teams are not yet fully internationally recognized, most likely because the field of myology is only beginning to emerge and because DRESS represents a rare disease, with only a small number of lab involved at the international level.

The unit does not have a full time researcher. Although many clinicians working in the unit (both Team 1 and 2) are very committed to research (both fundamental and clinical research) and fulfill top level student and PhD trainings, their teaching and clinical duties may hamper participation at prestigious meetings and joint lab meetings.

• Recommendations

Given the quality of science conducted in the Unit, the well-recognized expertise in clinical immunology of the 2 PIs at a national level, the good and well organized collaboration between people, it is anticipated that the Unit should benefit from full time researchers. One way to achieve this goal, and at the same time strengthening the Unit's international visibility and attractiveness to young researchers, would be via the organization of an International course on human Immunology research and/or organizing a conference on Autoimmunity.

Organize regular joint lab meetings to maintain the scientific discussion and social network between the 2 Teams. In addition, maintain good communication, quality of work and collaboration by a yearly retreat of the Whole unit.

Other recommendations include further investment in pathology validation of mouse models and prioritization of projects on rheumatoid arthritis.

• Production results 3  Specific comments

• Appreciation on the results

The overall scientific level of the unit is very good. Several discoveries are highly original and had or may have important clinical applications as proved by the different patent applications. Moreover training of PhD. is also very good with more than 10 students defended their thesis in the past 5 years. The unit has developed stable partnership notably through the establishment/use of different patient cohorts.

• Appreciation on the impact, the attractiveness of the research unit and of the quality of its links with international, national and local partners

Performance of the research unit has been very good with respect to scientific publications and patent applications. Multiple patents have been licensed. These research results are expected to positively impact socio-economic partnerships. In addition, the research unit is well capable to fund research activities with external grants. The international recognition is expected to grow if the recent upward momentum is maintained.

• Appreciation on the management and life of the research unit

Management of the research unit with respect to novel science and teaching is in place and performing a good job. There is an excellent atmosphere within the unit, with a noticeable contentment of students and ITA people. This is clearly due to the excellent management and availability of the director. However, the review committee feels that scientific meetings for the whole unit, with attendance of PhD students and staff from both teams, are not structurally planned. To insure cross-fertilization between the two teams, and to better support PhD training, it is recommended to plan such meetings regularly.

All researchers of the unit contribute greatly to teaching with an impressive participation and organization of courses for both medical and biological studies. The unit has also strongly invested in the local structuring of the research with the participation in the scientific committee to clinical research of the hospital, to the administration board of the university but also with the development of a flow cytometry facility open to the whole scientific community.

• Appreciation on the scientific strategy and the project

The overall strategy of the Unit is clearly defined and appears very good. The projects are innovative and use state-of-the-art technology. The investigators have the expertise and the appropriate collaborations needed for their research. The projects are feasible in their hands, although quite demanding. • Appreciation on the results

Team 1 worked on 3 major projects: immuno-myology, extracellular nucleotides and regulatory T cells, and functional genomics and pharmacogenomics of rheumatoid arthritis.

Very good output in terms of scientific publications, such as recent J Exp Med and Faseb J publications, and patents, such as patents for Myoarray and a quantitative assay for SRP antibodies. The number of PhD defences over the past 5 years is very good: indeed, the team has trained 7 PhD students and 11 Master students.

The muscle-specific models used or under construction in the immuno-myology project are original and have a clear impact on fundamental immunology and myology. The experimental mouse models of myositis so far developed are novel, likely relevant to the human disease, as affected mice develop paralysis reproducing human pathology. The results regarding CD8 T cell tolerance and endopasmic reticulum stress will also open up new avenues for clinical investigations based on these discoveries.

The rheumatology group has in parallel progressed in the identification of molecular markers of use for diagnostic or drug response prediction. The proteomic analysis of candidate antigens in rheumatoid arthritis are valued by the field of autoimmunity. The effort to identify biomarkers such as gene expression profiles that may predict responsiveness to biologics could have a large impact after further validation in additional groups of patients. Their access and use of large and well-validated patient cohorts is an obvious strength of their studies, allowing the identification and analysis of gene profiles that potentially predict therapy responses in the setting of rheumatoid arthritis.

The work on the ectonucleotide NAD, its receptor P2X7 and their action on regulatory T cells is well-performed, highly original, and has in all likelihood potential implications.

In seems that the scientific output of Team 1 has gone upward during the last year or two, which is obviously a very nice and healthy sign. The internal collaboration is stable and synergistic and certainly contributes to the high quality of the scientific output. The team comprises a very good combination of physician-scientists and basic scientists allowing them to conduct high-ranked translational research.

Collectively, the work from this team contributes original concepts to the fields of autoimmunity and T-cell tolerance.

• Appreciation on the impact, the attractiveness of the team and of the quality of its links with international, national and local partners

The leader of the team moved to Rouen on an AVENIR contract in 2005 and has since established a strong team and Unit. The ability of the Team members to raise funds is very good. They have good links with industrial partners, and an excellent ability to network and to establish the appropriate collaborations. It is anticipated that the international visibility of the team will be strengthened thanks to their recently published scientific achievements.

• Appreciation on the scientific strategy and the project

The focus of Team 1 on inflammatory muscle diseases is filling an important niche in France. The strategy and the planned projects are clear, well organized, relevant to human disease and feasible both from a scientific point of view and with regards to human and financial resources. The proposed projects including those improving these existing models are well constructed and feasible. The projects are original and some of them are truly cutting edge.

• Conclusion :

• Summary

The committee felt this is very good team doing translational research on muscle inflammatory diseases. The scientific output is on the rise. Most projects are cutting edge and should lead to original observations.

• Strengths and opportunities

The translational aspect and the good mix between basic and clinical research.

They occupy a unique niche.

• Weaknesses and threats

No full-time researcher with permanent position. A potential threat is a tendency to over-interpret the cinical value of established or yet to establish mouse models.

• Recommendations

Recruitment of a full-time researchers to ensure the positive momentum of the Team is highly recommendable, given the efforts invested and future plans to go from pre-clinical models towards good clinical research and development of novel diagnosis and therapeutic approaches in human diseases.

• Title of the team and name of the team or project leader • Appreciation on the results

Team 2 also worked on 3 projects: skin adverse reactions and T cell responses; role of TLRs in lupus erythematosus; and immune responses in patients treated with biological treatments.

Team 2 has a very good output in terms of scientific publications and clinical applications. The number of PhD defences over the past 5 years is good. Indeed, the team has trained 4 PhD students and 2 Master students.

The Team has made major contributions in the field of skin inflammatory disease pathophysiology and treatment over the last 4 years with major publications in top-tier journals such as N. Engl. J. Med. and Science Translational Medicine. Their novel finding that EBV production is triggered by DRESS-inducing drugs and that virus-specific T cells would be responsible for the very severe auto-inflammatory disease and skin lesions is highly innovative in the field of dermatology and has major clinical implications. Their efforts to sort and analyze B cells and autoantibody production in bullous pemphigoid patients is clearly of importance.

• Appreciation on the impact, the attractiveness of the team and of the quality of its links with international, national and local partners

The ability of members of Team 2 to raise funds is very good. They have gathered and access to good cohorts of patients both for rheumatoid arthritis (RA) and skin inflammatory diseases. They run the national reference center for autoimmune bullous skin diseases. The principal investigator for the RA projects has good links with industrial partners. Strong national and international collaborations have been developed, most notably with the Singapore immunology network. It is anticipated that the international visibility of the principal investigator will be strengthened thanks to the recently published scientific achievements.

• Appreciation on the scientific strategy and the project

The committee felt that the projects were of unequal relevance and originality. First, the projects related to the immune-mediated skin diseases (therapy, DRESS,…) are very well-defined, feasible, and highly relevant. Some of them are truly cutting edge. Second, the project investigating the contribution of the IL-10-producing B cell population in immune regulation in human autoimmune diseases is based on preliminary data and remains speculative. The planned experimental design may not be mature enough to lead to unambiguous answers. And lastly, the projects (based on strong preliminary clinical data) related to identification and validation of biomarkers and the study of their involvement in RA pathophysiology and prediction of responsiveness to given biotherapy (Adalimumab, Ethanercept, etc..) target very important questions and are highly relevant and represent a potential step toward personalized medicine.

• Conclusion :

• Summary

The committee felt this is a very good team performing translational research on skin inflammatory diseases and RA (although formally the latter disease is part of the team's future work).

• Strengths and opportunities

The translational value of their research and the good mix between basic and clinical research.

The past and present performance meets a high international standard in the field of skin autoimmunity. The scientific output is on the rise. Most projects are cutting edge and should lead to original observations.

They occupy an (inter)national niche with regards to autoimmune skin diseases.

There is an opportunity for further improved international recognition that the project leader should work on, and which should be feasible given his scientific output.

• Weaknesses and threats

No full-time researcher with permanent position.

Possibly too many projects related to RA (again this relates to the team's future work).

High risk with respect to the IL-10 producing B cells projects.

• Recommendations Make all possible attempts to recruit a full-time researcher.

Some caution should be taken about possible dispersion and projects may need to be better prioritized to allow more in-depth investigations. The committee suggests to limit the number of projects and to try to validate the very encouraging results obtained so far on independent cohorts of RA patients. We thank the visiting committee for its in-depth evaluation of our unit and its valuable comments. We were delighted that the teams have been found 'very good', and our work to have 'led to highly original results and novel concepts' with a clinical 'impact beyond doubt', and that 'the output of the unit is graded as very good' with regard to publications and patents. The very positive evaluation regarding 'excellent management', our 'overall strategy … clearly defined', the 'impressive … organization of courses for both medical and biological studies' and our '[strong investment] in the local structuring' were highly appreciated and very encouraging.

Regarding the recommendations:

-'Given the quality of science conducted in the Unit, the well-recognized expertise in clinical immunology of the 2 PIs at a national level, the good and well organized collaboration between people, it is anticipated that the Unit should benefit from full time researchers. One way to achieve this goal, and at the same time strengthening the Unit's international visibility and attractiveness to young researchers, would be via the organization of an International course on human Immunology research and/or organizing a conference on Autoimmunity.'

During the first quadrennial period, we have recruited in Team 1 one post-doc on a permanent position of associate professor (MCU) devoting the major part of his time to research, and recruited a senior MCU with habilitation (HDR) by mobility from another research laboratory. Also, the Director of the unit and the head of Team 2, despite their hospital and teaching duties, spend more than 50% of their time on research. As we indicated in the renewal application, we fully agree with the committee that recruiting full-time scientists on permanent positions is clearly one of our major goal for the next quadrennial/quinquennial period. For this, we will first recruit in the immuno-dermatology group of Team 2 one of our experienced post-doc (currently in Singapore) on a research engineer position that is now officially open for competition in 2011. He will have 100% time devoted to research. We also have another post-doc, already in the unit, that is planned for recruitment in the rheumatology group of Team 2 during the two-year period ahead on the same type of position, with an agreement in principle from Rouen University. In addition to two former PhD students currently on a post-doc position (US and Singapore), both teams actively develop their international relations with foreign research centers (Singapore, Hamburg, Buenos Aires and Cordoba notably) so as to facilitate the identification of senior research candidates.

We thank the visiting committee for its suggestion to organize a course/meeting on human immunology/autoimmunity to enhance our national and international visibility. A highly specialized workshop dedicated to immune tolerance and, more particularly, to immuno-myology and muscle autoimmune diseases would indeed help assign to our unit an original position in the field. We are now working on this project. For this, we will take advantage of the scientific relationship that we already have in the field and we will also benefit from the position of the Director of the unit who has recently been elected as Council Member of the International Union of Immunological Societies (IUIS, President S Kaufmann, former Presidents P Doherty and R Zinkernagel). This will favour networking. Also, the Director has been an active member of the organizing committee of a recent international meeting (1 st Franco-Argentine Immunology Congress FAIC 2010 in Buenos Aires). We are also in the process of participating to a European network on myositis, and another on AAV muscle gene therapy.

-'Organize regular joint lab meetings to maintain the scientific discussion and social network between the 2 Teams. In addition, maintain good communication, quality of work and collaboration by a yearly retreat of the whole unit.'

We are pleased that the committee has found the 'social and scientific atmosphere …very good'. Indeed, we have structured ourselves so that stimulating work-in-progress meetings are organized on a weekly basis at the level of each team/group and more formal presentations of finalized work are regularly given at the level of the Institute. We have developed many opportunities such as the weekly journal club, the Friday meeting at 12:pm and regular seminars with external speakers that allow members to exchange. Yet, we share the view of the committee that interaction between the 2 teams could be reinforced. We believe that this will be facilitated by our reorganization for the 2012-2015/16 period during which several current members of Team 1 will join Team 2.

In agreement with the committee's recommendation and our discussion during the site visit, we have organized a retreat on March 25 th (Cap Hornu, Baie de Somme) where every doctoral student presented his/her work (chairpersons were alternatively the doctoral students themselves) and largely discussed his/her projects with everyone. All unit members concurred to the success of this meeting that was considered by all as a very exciting experience of scientific and social exchange. There is no doubt that we are eager to reiterate this at least on a yearly basis.

-'Other recommendations include further investment in pathology validation of mouse models and prioritization of projects on rheumatoid arthritis.' While mouse models are by definition partly artificial, they remain invaluable tools for investigating disease pathogenesis. We have developed new experimental models such as SM-Ova (expression of a neo-autoantigen specifically in muscle), Inserm -Unité Mixte de Recherche U-905 Université de Rouen Faculté de Médecine et Pharmacie 22, Boulevard Gambetta 76183 -R O U E N Cedex 1 02.35.14.85.35 02.32.88.81.86 annie.pons@univ-rouen.fr Rag 0/0 x iMHC (crossing a model of muscle-specific inducible MHC-I expression to an immuno-deficient background) or new transgenic mice conditionally expressing a fusion H-2K b -β2m or H-2K b -β2m-Ovapeptide in muscle. We also use a model of spontaneous myositis in ICOS 0/0 NOD and ICOSL 0/0 NOD mice in collaboration with C Boitard (U986). The conjunction of these models will offer unprecedented opportunities to study the different aspects (immunological versus non immunological) of pathogenesis of the different forms of myositis. For higher clinical impact, we use these model in parallel to the analysis of muscle samples from patients that present with the corresponding forms of myositis. This is facilitated by our local recruitment of patients (Internal Medicine department, Dermatology department [for dermatomyositis] and Rheumatology department whose senior members are part of our unit) and by our collaboration with Pitié-Salpêtrière national reference center in Paris and the myology group of Henri Mondor hospital in Créteil.

For instance, we have discovered an unexpected role of endoplamic reticulum stress causing severe myopathy in mice and there is now published evidence that a similar phenomenon occurs in selected forms of myositis. Therefore, we are currently studying a series of relevant patients' muscle samples to reinforce the pathological relevance of our experimental work. Also, in a paper recently published in Arthritis and Rheumatism, we have suggested an unexpected pathogenic role of anti-SRP autoantibodies in a severe form of necrotizing myopathy in humans. We are currently investigating this in a mouse model (injection of auto-antibodies from patients) and perform in-depth pathological studies of both mouse and human muscle samples with the clear view that mouse models should be conducted in parallel to human studies.

Regarding prioritization, we have spent significant efforts to focus our projects on a more limited number of objectives than during the first quadrennial period. Team 1 will concentrate only on selected projects in immuno-myology and biotherapy of muscle diseases, and Team 2 on a autoimmune bullous skin disease and mechanisms of drug reaction. The rheumatology group in Team 2 will concentrate on a single inflammatory disease e.g. rheumatoid arthritis with complementary human and mouse studies. Among the numbers of targets that we evidenced from our transcriptomic/proteomic analyses, we have been very selective to choose only two of them for further comprehensive analysis in mice (RasGRP and α-enolase) that correspond to current PhD work. When these PhDs are completed, we will stringently consider the pursuit of these projects depending on the results obtained.

•

  Date and execution of the visit

Team 2 "

 2 Physiopathology and innovative therapies of immuno-dermatological diseases", directed by Philippe MUSETTE, studies the physiopathological mechanisms of autoimmune dermatological disorders and drug-induced toxidermia through experimental models and clinical studies in collaboration with the Reference Center of bullous cutaneous autoimmune diseases directed by Pascal JOLY. The research of this team focuses on the understanding of the role of T cells in drug-induced eruptions and viral reactivation on T cell activation, as well as the analysis of Toll-like receptors and their implication in the development of the autoimmune B cell responses in lupus erythematosus. Finally, the team has conducted biological and clinical studies to assess the efficacy of an anti-CD20 monoclonal antibody in the treatment of patients with pemphigus.

(

  cf. http://www.aeres-evaluation.fr/IMG/pdf/Criteres_Identification_Ensgts-Chercheurs.pdf) A1: Number of permanent researchers with teaching duties (recorded in N1) who are active in research 11 A2: Number of permanent researchers without teaching duties (recorded in N2) who are active in research 0 A3: Ratio of members who are active in research among staff members [(A1 + A2)/(N1 + N2)] 100% A4: Number of HDR granted during the past 4 years 0 A5: Number of PhD granted during the past 4 years 10

4

  Appreciation team by team and/or project by project projet• Title of the team and name of the team or project leader Team 1 Immunopathology and biotherapy of muscle diseases Olivier BOYER • Staff members Past Future N1: Number of researchers with teaching duties (Form 2.1 of the application file) 6 N2: Number of full time researchers from research organizations (Form 2.3 of the application file) 0 N3: Number of other researchers including postdoctoral fellows (Form 2.2 and 2.4 of the application file) 1 N4: Number of engineers, technicians and administrative staff with a tenured position (Form 2.5 of the application file) 3 N5: Number of engineers, technicians and administrative staff without a tenured position (Form 2.6 of the application file) N6: Number of Ph.D. students (Form 2.7 of the application file) N7: Number of staff members with a HDR or a similar grade 5

  Team 2 Immunopathology and innovative therapy of joint and skin diseases

	Philippe MUSETTE
	• Staff members
	Past	Future
	N1: Number of researchers with teaching duties (Form 2.1 of the	3
	application file)
	N2: Number of full time researchers from research organizations (Form 2.3 of the application file)	0
	N3: Number of other researchers including postdoctoral fellows (Form 2.2 and 2.4 of the application file)	3
	N4: Number of engineers, technicians and administrative staff with a tenured position (Form 2.5 of the application file)	5
	N5: Number of engineers, technicians and administrative staff without a tenured position (Form 2.6 of the application file)
	N6: Number of Ph.D. students (Form 2.7 of the application file)

N7: Number of staff members with a HDR or a similar grade 3

Sciences du Vivant et Environnement

				Statistiques de notes globales par domaines scientifiques
						(État au 06/05/2011)
	Note globale	SVE1_LS1_LS2	SVE1_LS3	SVE1_LS4	SVE1_LS5	SVE1_LS6	SVE1_LS7	SVE2 _LS3 *	SVE2_LS8 *	SVE2_LS9 *	Total
	A+		7	3	1	4	7	6		2		30
	A		27	1	13	20	21	26	2	12	23	145
	B		6	1	6	2	8	23	3	3	6	58
	C		1					4				5
	Non noté	1									1
	Total	42	5	20	26	36	59	5	17	29	239
	A+		16,7%	60,0%	5,0%	15,4%	19,4%	10,2%		11,8%		12,6%
	A		64,3%	20,0%	65,0%	76,9%	58,3%	44,1%	40,0%	70,6%	79,3%	60,7%
	B		14,3%	20,0%	30,0%	7,7%	22,2%	39,0%	60,0%	17,6%	20,7%	24,3%
	C		2,4%					6,8%				2,1%
	Non noté	2,4%									0,4%
	Total	100,0%	100,0%	100,0%	100,0%	100,0%	100,0%	100,0%	100,0%	100,0%	100,0%
	*
			Intitulé UR / équipe		C1	C2	C3	C4	Note globale
	PHYSIOPATHOLOGIE ET BIOTHÉRAPIES DES MALADIES INFLAMMATOIRES ET AUTOIMMUNES	A+	A	A+	A	A
	PHYSIOPATHOLOGY AND BIOTHERAPIES OF IMMUNE
	PATHOLOGIES OF LOCOMOTOR APPARATUS [BOYER-	A	A	Non noté	A+	A
			BOYER]
	PHYSIOPATHOLOGY AND INNOVATIVE THERAPIES OF
	IMMUNO-DERMATOLOGICAL DISEASES [BOYER-	A+	A	Non noté	A	A
			MUSETTE]
	C1	Qualité scientifique et production
	C2	Rayonnement et attractivité, intégration dans l'environnement
	C3	Gouvernance et vie du laboratoire
	C4	Stratégie et projet scientifique

les résultats SVE2 ne sont pas définitifs au 06/05/2011. Intitulés des domaines scientifiques Sciences du Vivant et Environnement • SVE1 Biologie, santé SVE1_LS1 Biologie moléculaire, Biologie structurale, Biochimie SVE1_LS2 Génétique, Génomique, Bioinformatique, Biologie des systèmes SVE1_LS3 Biologie cellulaire, Biologie du développement animal SVE1_LS4 Physiologie, Physiopathologie, Endocrinologie SVE1_LS5 Neurosciences SVE1_LS6 Immunologie, Infectiologie SVE1_LS7 Recherche clinique, Santé publique • SVE2 Ecologie, environnement SVE2_LS8 Evolution, Ecologie, Biologie de l'environnement SVE2_LS9 Sciences et technologies du vivant, Biotechnologie SVE2_LS3 Biologie cellulaire, Biologie du développement végétal Inserm -Unité Mixte de Recherche U-905 Université de Rouen

	Faculté de Médecine et Pharmacie
	22, Boulevard Gambetta
	76183 -R O U E N Cedex 1
	02.35.14.85.35
	02.32.88.81.86
	annie.pons@univ-rouen.fr


Evaluation report

This report is the sole result of evaluation by the expert committee, the composition of which is specified below.

The assessments contained herein are the expression of an independent and collegial reviewing by the committee.

Unit name:

Microbiotas, Hosts, Antibiotics and Bacterial Resistances

 Introduction History and geographical location of the unit

The MiHAR team is part of the unit "Thérapeutiques cliniques et expérimentales des infections" (EA3826) headed by Mr Gilles POTEL which plans to split into two separate units: MiHAR as a new unit and EA 3826. MIHAR is located at the same place than the EA3826 on the 4 th floor of the Faculty of Medicine. The group will move in 2016 in the new "Institut de Recherche en Santé" (IRS-2) on the Nantes Island.

Management team

The MIHAR team intends to work in a new separate unit that will be headed by Mr Eric BATARD and Mr Didier PELLETIER.

HCERES nomenclature

SVE1-LS6

Scientific domains

The scientific domain of MiHAR is the relationship between microbiota, the hosts (human and animals), the antibiotics and the consequences on antimicrobial resistance. The unit will focus on the relationship between digestive tract microbiota and enterobacteria resistance to cephalosporins, penems and quinolones.

Unit workforce

Unit

Introduction

The MiHAR group results from the split of the EA3826 in two teams. MiHAR recently became independent and choosed to focus on antibiotic resistance and microbiota. Between 2010 and 2015, the research activities have been divided in two, epidemiological analysis of microbial resistance and training and acquisition of techniques designed to perform microbiota analysis. For the next contract, the initial team members will be joined by researchers from Nantes and Angers in order to build a motivated group working on microbiota, host, antibiotics and microbial resistance. The report is globally heterogenous reflecting the "in progress" phase of the unit.

Global assessment of the unit

MiHAR itself does not exist per se and cannot be evaluated as an entity. The data presented to the committee reflect the individual activity of each team partner, providing the committee a good perspective of their potential complementarities that may become a strength in the future. The former research represented by the unit members, focused on 5 main themes. The first one is the epidemiological surveillance of enterobacteria resistance to beta-lactams and fluoroquinolones: this is mainly a hospital-based study. The second one is the analysis of antibiotics prescription and consumption. In a third theme, the group explored the relationship between antibiotic, host and bacterial resistance, and the group successfully generated a pharmaco-epidemiological approach from the raw data, with potential consequences in the clinical management of antibiotic therapy. The 4 th topic is based on the analysis of the gut microbiota: a member of the team was trained in Mineapolis to learn the techniques that could be implemented in Nantes. Finally, the group studied the modulation of the interactions between microbiota/host and antibiotics: this last topic aims at exploring the relationship between antibiotic duration and resistance generation.

The individual assessment of each of these themes shows potential to build a new team. The MiHAR unit proposes to study the interactions between host and microbiota and the consequences on resistance after antibiotic treatment. Their goal is to modulate these interactions, to control the resistance and propose therapeutic strategies. As an ultimate goal of their project, the group proposes to optimise the antibiotic treatment based on personalized microbiota analysis.

The committee feels that it is too early to create an individualized entity; the MiHAR group is not yet completely mature.

Strengths and opportunities in the context

The MiHAR group associates a large number of people with many complementary expertises, who take part in potent local and national networks (involvement in nine national multicentric studies). Antibiotic resistance is currently a major problem at the national and international levels. Therefore, national societies and the French high authority for health (HAS) provided clear recommendations to fight antibiotic resistance and promote antibiotic good use and stewardship. The goals of MiHAR therefore perfectly match with the national objectives.

Weaknesses and threats in the context

The MiHAR unit is very young and has not yet the experience to work and publish as an entity. By analysing the project, the committee noted several major limitations. The first goal seems feasible, but the link between the epidemiological data obtained and the goal of the group was not clearly described.

Concerning the analysis of the microbiota and the optimisation proposed, the amount of data to be generated along with several different potential conditions (various types of colonization, relative quantity of resistant pathogens…) seems rather ambitious and needs to be restricted. Another limitation is the microbiota analysis itself, with such a very limited specific staff (lack of biostatisticians) in the context of a serious international competition.

The need of animal models and the basic research project were not detailed. Moreover, the relevance of the use of animal models was not convincing.

Looking at the structure, the MiHAR group just emerged from the EA3826. The group has neither technical staff, nor full time researcher. This hampers the feasibility of the project in regard of the schedule. Finally, the project has not yet got any funding.

Recommendations

The committee recommends having a more specific, detailed and focused project in the context of a hot topic (relationship between microbiota, antibiotic treatment and infection occurrence) and proposing a detailed program for the recruitment of the manpower and expertise requested to achieve the project (Biostatistician, Microbiologist, Lab technicians).

Since some unit members are located at a 100 km distant laboratory, a weekly meeting (at least by videoconference) and a single database gathering all documents from the unit should be implemented.

  Mr Antoine ANDREMONT, Hôpital Bichat Claude Bernard, Paris Mr Ferhat MEZIANI, Université de Strasbourg, Strasbourg Scientific delegate representing the HCERES: Ms Catherine SCHUSTER Representatives of supervising institutions and bodies: Mr Fréderic BEN HAMOU, Université de Nantes MS Brigitte DRENO, Université de Nantes Head of Doctoral School: Ms Corinne MIRAL, Doctoral School ED n°502, "Biologie-Santé".

  Permanent researchers from Institutions and similar positions N3: Other permanent staff (technicians and administrative personnel) 5 (1.1 FTE) N4: Other professors (Emeritus Professor, on-contract Professor, etc.) N5: Other researchers from Institutions (Emeritus Research Director, Postdoctoral students, visitors, etc.) N6: Other contractual staff (technicians and administrative personnel)

Postdoctoral scientists having spent at least 12 months in the unit Number of Research Supervisor Qualifications (HDR) obtained during the period