BACKGROUND METHODS Drug Development Decision Rules Product Profile Maps As a key component of model based drug development (MBDD), quantitative decision criteria (QDC) provides the important link between evidence synthesis (metaanalysis and/or PK-PD-disease progression modelling) and the assessment of future trial performance (1). Application within the MBDD framework across learning and confirming phases of development has recently been more thoroughly examined (2-3). Model based meta-analysis (MBMA) of literature data (4,5) and additional relevant data from Pfizer internal studies were used to develop product profile maps and enable the determination of target values used in the QDC. PH-797804 & Design PH-797804 is a potent and selective orally active inhibitor of p38 mitogen activated protein (MAP) kinase which regulates the production and downstream signaling of pro-inflammatory cytokines and has a role in regulating neuronal plasticity and pain sensitisation. In evaluating its potential in the treatment of chronic NcP, a POC study has been designed to evaluate its efficacy (in presence and absence of naproxen) in relieving pain in patients with osteoarthritis (OA) of the knee. Primary endpoint WOMAC pain subscale 0-10 numeric rating scale (NRS). Efficacy Priors for PH-797804 Operating Characteristics (OC) Both conditional (based on assumed ∆) and unconditional (integrated across P(∆|(prior data & translational uncertainty)) operating characteristics were evaluated across a range of design assumptions (n, SD and Prior). While the two decision rules could be optimized to provide a go decision based a similar observed value, the operating characteristics were shown to be dependent on the design (sample size) and the assumed P(∆|(prior data & translational uncertainty).  Lalonde RL .etal (2007) Model-based drug development Clinical Pharmacol Ther 61:275-291  Smith MK, etal. (2011) Decision-Making in drug development: Application of a model based framework for assessing trial performance P 61- 83 Clinical Trial Simulations, AAPS Advances in the pharmaceutical Sciences series 1. Kimko H.H.C and Peck.C.C (eds), Springer.  Chuang stein etal (2011) A quantitative Approach for making go/no-go decisions in drug development Drug Information Journal (45)187-202  Rappaport BA, etal . ACTION on the prevention of chronic pain after surgery. Anesthesiology 2010;112:509–10.  Dworkin RH, etal Evidence-based clinical trial design for chronic pain pharmacotherapy:A blueprint for ACTION PAIN (in press Available online 9th December 2010) Boucher M, A Bayesian Meta-Analysis of Longitudinal Data in Placebo Controlled Studies with Naproxen, PAGE 2008. http://www.pagemeeting.org/pdf_assets/8269-Bayesian%20Meta%20Analysis%20Final.pdf  Ezzet F Modeling Adverse Event Rates of Opioids for the Treatment of Osteoarthritis Pain using Literature Data.PAGE 2010 http://www.page-meeting.org/pdf_assets/1411OA%20Pain%20PAGE%20Poster%202010.pdf **The authors would like to thank Martin Boucher and Tracy Higgins Pfizer Ltd for the meta-analyses which underpin the work presented -1.5 -0.6 Optimistic Prior PH-797804 -2.0 -1.8 Realistic Prior PH-797804 density 0.005 0.010 0.015 0.030 0.025 0.020 0.0 -4 -2 0 2 4 6 -6 -4 -2 TrueTrue Difference Value 0 2 4 6 TrueTrue Difference Value Conditional OCs a)Pr(∆> SOC) 95% b) Pr(∆> SOC*1.75) 25% 1.75*SOC SOC SOC Go Amber (notable analgesia) Stop True Difference True Difference Minimum Observed Mean value for Go (SD=1.5) Unconditional OCs a) (Pr(∆> SOC) 95%) b) (Pr(∆> SOC*1.75) 25%) Realistic Prior Optimistic Prior PPV= Positive predictive value NPV= Negative predictive value Evaluation of Trial Sensitivity for Go Decision A sensitivity of the proposed design and decision rules (b) to detect an increase in treatment effect over SOC across baseline values, placebo/SOC efficacy and background rate of non-response was undertaken. A non-response/dropout rate of 30% was assumed based on past experience. It was determined that the design was able to detect a mean change required for a Go decision (Pr(∆> SOC*1.75) 25%) provided the inclusion criteria target a population with a mean baseline NRS score of > 6 (moderate to severe pain population). DISCUSSION -2.5 -1.2 RA to OA Translational uncertainty 0.015 -6 Evidence of notable analgesic efficacy was defined as: Pr(∆> placebo) 90% & Pr(∆> SOC) 20% Two competing decision rules governing the Go Decision, progression of PH-7978040 to a dose ranging study, were evaluated: a) High confidence of greater efficacy over SOC (Pr(∆> SOC) 95%) b) Lower confidence of achieving the TV which is superior to SOC (Pr(∆> SOC*1.75) 25%). The within Subject SD was estimated to 1.5 from previous trials. Sample sizes of 16 (short dash line), 33 (solid-line), 66(long dash line) per group are compared. TV 1.58 Patients on NSAIDs Change in WOMAC Pain Score (0-10 scale) ** 0.0 QDC Oxycodone ER -1.0 0.010 A previous RA POC study had been conducted for PH-797804 and a break down of treatment effect by background NSAID usage was available. Prior data on NSAID and COX2 indicated that pain efficacy in RA and OA patients were approximately similar. A combination of this information with the meta-analyses for SOC were used to predict the expected treatment effect for PH-797804 in OA patients with/without NSAIDs. In addition, an empirical estimate for the translational uncertainty associated with a new MOA was factored in to develop a realistic design prior. Nevertheless, selection was largely influenced by the philosophy of identifying a higher hurdle and allowing progression to phase 2b provided there is reasonable evidence to indicate that this could be achieved in later development. • To design a POC study for PH-797804 in patients with OA of the knee with a high probability of making the correct decision at the end of the trial. •To highlight some of the considerations in the context of developing robust quantitative decision criteria in the assessment of novel therapies for the treatment of chronic nociceptive pain (NcP). -0.5 0.0 0.0 While the choice of rule b) over rule a) was supported by the operating characteristics: •Slightly better OC with larger sample sizes( n=66) •Control of type 1 error across sample size (Unconditional OC’s) •Minimize probability of Amber outcome OBJECTIVES Patients not on other Tx Change in WOMAC Pain Score (0-10 scale) * Naproxen * 1.75 SOC= -0.9 Density density The challenge of low yield and generic competition is a harsh reality of modern drug development. In this regard, despite considerable investments, the hurdles facing novel analgesic drugs are particularly high. For the treatment of chronic nociceptive pain (NcP) there remains limited therapeutic options, (essentially acetaminophen, NSAID or opioids) and patients continue to be inadequately treated. Differentiation from these agents is a clear goal for early analgesic drug development. Efficient early stage screening is required in order to prevent late stage clinical or commercial failure. Quantitatively robust product concepts are needed to provide the foundation for effective decision-making. Criteria need to efficiently screen for analgesics which have sufficient signal to warrant further investment; where their potential can be enhanced upon identifying the optimal dose regimen in a phenotypically targeted patient population. Target Range Compound and Indication: PH797804 for Chronic musculoskeletal pain Patient population: OA All efficacy reported as PBO-corrected. Assume baseline pain score ~7 on 0-10 NRS scale & placebo response of 1-2 pts Frequency Analgesic Drug Development Challenge RESULTS 0.005 Developing quantitative decision rules for novel analgesic drugs: A case study illustrating current experiences and learnings Authors: Scott Marshall(1), Simon Kirby(1), Anna Crossland(1), Paul Sanders(1), Joe Picard(2), and Bernadette Hughes(1). Institutions: (1) Pfizer Ltd, Sandwich, Kent, UK; (2) Pfizer Ltd, New London, CT, USA * EOT= End of treatment mean NRS score ** Based on analysis of previous parallel group trials In response to the current decline in the approval of new analgesic medicines the FDA has recently launched the Analgesic Clinical Trial Innovations, Opportunities, and Networks (ACTION) initiative with the aim ‘‘to streamline the discovery and development process for new analgesic drug products for the benefit of the public health’’ (4). Study design factors (e.g. increasing placebo response, loss of assay sensitivity) malign the drug development process of novel analgesics. The concept of an evidence-based approach to the design of analgesic clinical trials with the aim of first understanding the relationships between trial characteristics and outcome has been proposed (5). This case study illustrates the role that quantitative decision criteria can have in enabling such scrutiny in order to prevent future trial design failure. Thorough assessment of analgesic trial characteristics is similarly required in order to ensure product concepts can be adequately tested. This work also highlights the clear role that unconditional operating characteristics have in helping to assess proposed quantitative decision criteria.