Towse NDDP implications for drug development
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This document discusses a new drug development paradigm (NDDP) that aims to improve the efficiency and effectiveness of clinical drug development. It outlines several proposals that call for reforming the current drug development model, including using more modeling, adaptive trial designs, and integrating clinical trials into healthcare delivery systems. The NDDP proposes a more flexible framework with early patient/payer engagement, exploratory and confirmatory research phases using modern trial designs, and post-approval studies to establish relative value. Challenges for industry include conducting large simple trials, partnering to support more efficient trials, and having a clear evidentiary strategy tailored to different drug archetypes.
![The research leading to these results has received support from the Innovative Medicines Initiative Joint Undertaking under grant
agreement no [115303], resources of which are composed of financial contribution from the European Union’s Seventh Framework
Programme (FP7/2007-2013) and EFPIA companies’ in kind contribution.
www.imi.europa.eu
Background
RWE on
disease,
treatments,
care pathways,
unmet need
etc
Post Launch
RWE on: use of
new medicine,
relative
effectiveness,
longer term
outcomes
Potential Value Confirm Value
Comparative Trials. Pragmatic Trials, giving
information on effectiveness
More Focussed Context for current care and
outcomes to inform initial assessments
Evidence Synthesis to combine all sources of
information: RCT + PCT + OBS
Predict Value of new Medicine
How much can be done pre-launch?
Or should we get to Post-Launch sooner?
Before phase3 During phase3 After Launch](https://image.slidesharecdn.com/towsenddpimplicationsfordrugdevelopmentv1-150619143209-lva1-app6892/85/Towse-NDDP-implications-for-drug-development-2-320.jpg)
Towse NDDP implications for drug development
- 1. THE NDDP PROJECT – IMPLICATIONS FOR DRUG DEVELOPMENT Adrian Towse
- 2. The research leading to these results has received support from the Innovative Medicines Initiative Joint Undertaking under grant agreement no [115303], resources of which are composed of financial contribution from the European Union’s Seventh Framework Programme (FP7/2007-2013) and EFPIA companies’ in kind contribution. www.imi.europa.eu Background RWE on disease, treatments, care pathways, unmet need etc Post Launch RWE on: use of new medicine, relative effectiveness, longer term outcomes Potential Value Confirm Value Comparative Trials. Pragmatic Trials, giving information on effectiveness More Focussed Context for current care and outcomes to inform initial assessments Evidence Synthesis to combine all sources of information: RCT + PCT + OBS Predict Value of new Medicine How much can be done pre-launch? Or should we get to Post-Launch sooner? Before phase3 During phase3 After Launch
- 3. SOME RECENT CALLS FOR CHANGE
- 4. • Barker urges industry to move to a “learn and confirm” model • Orloff et al.argued for a radical redesign to reduce development costs with (i) more use of biological, pharmacological, and statistical modelling and simulation to fine tune study requirements, and (ii) adaptive trial design • The President’s Council of Advisors on Science and Technology (PCAST) Report recommended reengineering the clinical trials system • Califf et al.also focused on the need for clinical trials to be integrated into the health care delivery system rather than research and delivery being regarded as separate enterprises. • EHRs provide a means for both identifying patients for recruitment into clinical trials and for following patients in clinical trials reducing the costs of implementing trial protocols. PROPOSALS FOR REFORM
- 5. PROBLEMS WITH THE CURRENT DRUG DEVELOPMENT PARADIGM 5
- 6. A FLEXIBLE BLUEPRINT FOR MEDICINES DEVELOPMENT New flexible blueprint for medicines development Exploratory R & D Review & design Confirmatory trials Key Characteristics of changed model Flexibility to design the process around the medicine Reduced bureaucracy Alignment on approach between regulators and innovators Single flow of learning, not fragmented Patients perspective and access needs designed in Submit & confirm approval Patient Access Studies to establish relative value Early access on condition of data collection Source: Barker, R. 2030 The Future of Medicine: Avoiding a Medical Meltdown. 2010
- 7. A NOVEL MODEL FOR CLINICAL DEVELOPMENT Target discovery and validation PoC Clinical Trials Clinical Development Exploratory Phase Confirmatory Phase • Apply biomarkers, modeling and simulation and advanced statistical methodology • Demonstrate PoC and establish dose selection • Apply innovative tools and clinical trial designs such as adaptive or seamless studies • Identify target patient populations and confirm optimal dose; establish the benefit/risk ratio Target PoC Approval Orloff et al. Nature Reviews Drug Discovery 2009
- 8. A STRATEGY FOR CER AND MARKET ACCESS Phase I/II Phase IIIa Phase IIIb Phase IVa Phase IVb CER Trials/PCTs Registries Modeling/indirect comparisons Physiology RCTs Claims data monitoring Feedback Loop Adapted from Schneeweiss et al. CPT 2011
- 9. DEVELOPING A NEW DRUG DEVELOPMENT PARADIGM RESPONDING TO THE CHALLENGE OF CER AND RE IN THE US AND EUROPE
- 10. OVERALL PROCESS NDDP Defining Future CER Environment in US Defining Future RE Environment in Europe Payer Perspectives In US and Europe Current Drug Development Paradigm In US and Europe
- 11. WHAT IS NEW ABOUT THE ENVIRONMENT WE DESCRIBE? • Greater acceptability of enrichment designs and surrogate endpoints for regulatory approval • Patient-powered research networks and country-sponsored registries • Selected pockets of healthcare systems and some countries with reliable mechanisms to track patients healthcare use across settings of care and longitudinally through clinically-rich electronic health records • Greater harmonization between regulatory agencies and HTA bodies in Europe
- 12. DEFINITIONS Term Definition Adaptive Design A design that allows the modification of the trial and/or statistical procedures during the conduct of a trial, based on the review of interim data. The purpose of an adaptive design is to increase the probability of success without undermining the validity and integrity of the trial. (Chow et al. al. 2008) Confirmatory Trials As compared to the traditional approach to drug development that separates clinical development into sequential phases, an integrated model aims at improving the effectiveness of clinical development process by increasing flexibility and maximizing the use of accumulated knowledge. In this model, broader, more flexible phases leading to submission for approval are designated ‘exploratory’ and ‘confirmatory’ In the confirmatory phase, modern designs, tools and knowledge are applied to larger-scale studies with the goal of identifying the target patient population in which the drug is efficacious, establishing the benefit/risk ratio and confirming the optimal dose and dosing regimen. During this phase, innovative clinical trial designs such as adaptive or seamless studies compress timelines, improve dose and regimen selection, and reduce the number of patients assigned to non-viable dosing regimens.(Orloff et al. 2009) Exploratory Research See “Confirmatory Trials” for explanation of the model. During the exploratory phase of development, this model uses all available knowledge and tools, including biomarkers, modelling and simulation, as well as advanced statistical methodology. Trials are designed to determine proof-of-concept (Poc) and to establish dose selection to a level of rigour that will enhance the likelihood of success in the confirmatory phase.(Orloff et al. 2009) Large Simple Trials A prospective, randomized controlled trial that uses large numbers of patients, broad inclusion criteria, multiple study sites, minimal data requirements, and electronic registries. Its purpose is to detect small treatment effects, gain effectiveness data, improve external validity. (Peto et al. 1993) Pragmatic Clinical Trial PCTs are randomized controlled trials that can rigorously evaluate the risks, benefits, and costs of treatment interventions as they occur in “real-world” settings and for heterogeneous, “real-world” patients. Results can be very relevant to healthcare decision makers. (Chalkidou, et al. 2012). Proof of Concept Studies See “Confirmatory Trials” for explanation of the model. During the exploratory phase of this model, trials are designed to determine proof of concept (PoC) and to establish dose selection to a level of rigour that enhances the likelihood of success in the confirmatory phase. (Orloff et al. 2009) Registry An organized system that uses non-experimental study methods to collect uniform data (clinical or other) to evaluate specified outcomes for a population defined by a particular disease, condition, or exposure, and that serves one or more predetermined scientific, clinical, or policy purposes. Sequential Cohort Studies Sequential cohort design begins tracking utilization and resource use through administrative and electronic health record data as soon as a drug gains market access. (Schneeweiss et al. 2011). Sequential cohorts are defined for calendar intervals, such as quarters, in order to balance temporal selection bias that may occur with new use of a drug (e.g., it may be used only in most difficult to treat population at the outset).
- 13. PRODUCT ARCHETYPE # 1: BREAKTHROUGH DRUG A new breakthrough drug of relatively high cost that is effective in a small population of patients who suffer from a common disease but have a specific biomarker identified by a companion diagnostic test “Supportive data in broader population may be observational (if rigorous) with a strong, plausible biologic case for a broader population.” “If diseases are common, we expect more rigor.” (Demand for RCTs in broader population may depend on therapeutic area & available treatments) HTA bodies – would expect ‘prospective’ observational study Payers – would likely restrict coverage to population with predictive marker. May use own data to evaluate “indication creep.” ACO – would consider partnership to study in broader population.
- 14. PRODUCT ARCHETYPE # 1 BREAKTHROUGH DRUG A new drug that is a breakthrough for treating patients who suffer from a common disease, but has been studied only in a small population that has a specific predictive biomarker identified by a companion diagnostic test. Example: Lipid-lowering drug studied in patients with familial hyperlipidemia Ultimate potential use would be statin users in the general population
- 15. NEW DRUG DEVELOPMENT PARADIGM FOR 2020: MOST LIKELY SCENARIO FOR CER/RE New Seamless Framework Exploratory Research Confirmatory Trials Patient/Payer Engagement Approval Key Features • Patient/payer engagement early to ensure outcomes reflect those of importance to them • Smaller targeted trial brings drug to market earlier • Bayesian/adaptive designs to improve efficiency of trial development throughout the life cycle with clear decision points after each round of evidence development • Second trial in broader population is large simple trial with focused question • EMA requirements for post-authorization efficacy studies can be built into the second trial • Sequential cohort studies initially used to track off-label use; data used to design second trial Modeling, simulation, Proof of concept trials Enrichment, Adaptive Designs Sponsor Activities Partnerships RCT Biomarker+ Reimbursement LST Population 2 Pivotal Trials Archetype 1: Breakthrough drug studied only in small population with biomarker Sequential Cohort Studies Open Label
- 16. DRUG DEVELOPMENT PROGRAM FOR BREAKTHROUGH DRUG STUDIED ONLY IN A SMALL POPULATION WITH BIOMARKER: MOST LIKELY SCENARIO Study Design Phase of Drug Development Goal Modeling studies/Enrichment, Adaptive Design Trials Exploratory Research/Confirmatory Trials Define the populations in which impact on outcomes is greatest; Observational Studies/Registry Exploratory Research Understand patterns of use in broader population, begin to understand subgroups for additional indications; Patient registry opportunity to explore associations of biomarker with outcomes identify population for enrollment RCT First pivotal trial in biomarker positive population Early market access with small targeted trial measuring surrogate outcome Observational Studies Post-regulatory for narrow population Partner with payers/patient advocacy groups to help them ensure use is consistent with label; better design second trial LST Second pivotal trial Streamlined data collection to enable access to broader population, safety, hard outcomes Sequential Cohort Studies Post-regulatory for broader population Continue partnerships to better define resource/outcome impact for pricing differential
- 17. PRODUCT ARCHETYPE # 2: “ME-TOO” NEW DRUG IN CROWDED, COMPETITIVE MARKET A new drug in a crowded, competitive market for a common chronic disease with a demonstrated effectiveness similar to its competitors. The manufacturer has identified several potential subgroups where the drug may be more effective; however, those subgroup analyses were underpowered and not planned a priori. Of the subgroups examined post hoc, one group was patients who did not improve on their initial therapies US payers: new drugs with similar effectiveness as competitors would be tiered at the same level Prefer RCT data with prospectively identified subgroups sufficiently powered to be considered for premium pricing: “Won’t accept underpowered subgroup analysis from pharmaceutical industry other than hypothesis generating for more pharma studies.” Peer-reviewed, prospective observational cohort studies may be acceptable, with these caveats: oObservational study should follow individuals from original drug trial , compare patients on competitor drugs oSubgroup findings should be consistent with the existing biological argument and supportive of existing knowledge Those not accepting observational studies concerned about manufacturers providing the evidence, publication bias and underpowered subgroup analysis
- 18. PRODUCT ARCHETYPE #2: NEW DRUG IN A CROWDED, COMPETITIVE MARKET A new drug in a crowded, competitive market (including generic alternatives) for a common chronic disease with a demonstrated efficacy similar to its competitors. The manufacturer has identified several potential subgroups where the drug may be more effective; however, those subgroup analyses were underpowered and not planned a priori. Of the subgroups examined post hoc, one group was patients who did not improve on their initial therapies. Example: Rheumatoid Arthritis drug that has the potential to demonstrate superior efficacy in patients who have failed treatment with market leader
- 19. NEW DRUG DEVELOPMENT PARADIGM FOR 2020: MOST LIKELY SCENARIO FOR CER/RE New Seamless Framework Exploratory Research Confirmatory Trials Approval Key Features • Patient/payer engagement early to ensure outcomes reflect those of importance to them • Adaptive designs not just for dosing, but for subgroups with clear decision points after each round of evidence development • Use of observational data helpful to identify subgroups • Some potential to partner with payers/health systems for adaptive access in collecting observational data demonstrating improved use of health care outcomes/resources/cost • EMA requirements for some post-authorization efficacy studies met through observational data Modeling, simulation, Proof of concept trials Adaptive designs Sponsor Activities Partnerships Pivotal RCT Reimbursement Indirect comparisons Archetype 2: Crowded competitive market, studied in large population, with potential superiority in subgroup Patient/Payer Engagement Preferred Pricing Sequential Cohort Studies
- 20. DRUG DEVELOPMENT PROGRAM FOR A DRUG IN A CROWDED COMPETITIVE MARKET, STUDIED IN LARGE POPULATION, WITH POTENTIAL SUPERIORITY IN SUBGROUP: MOST LIKELY SCENARIO Study Design Phase of Drug Development Goal Modeling/simulation indirect comparisons Exploratory Research Identify appropriate comparators; target effect sizes; Adaptive designs, RCTs Confirmatory trials Begin to understand subgroups with potential for larger effect sizes RCT (LST?) Pivotal trial Come to market with the broadest potential target group Open label follow up Post-regulatory Follow patients originally randomized and compare with observational cohorts to populate indirect comparison models Indirect comparisons Post-regulatory Meet diverse payer needs for different comparators Sequential Cohort Studies Post-regulatory Adaptive access partnerships to identify subgroups for improved tier placement, premium pricing; meet EMA PAES
- 21. WHAT TYPE OF CER/RE SHOULD DRUG COMPANIES INVEST IN BY 2020, AT WHAT STAGE OF DRUG DEVELOPMENT? Payers will still demand randomized studies -Patient registries will enable better design of trials, faster enrollment, drug companies can help facilitate their development -Adaptive designs will be more acceptable and will improve efficiency of early phase drug development -Indirect comparisons will be acceptable when there is biologically plausibility in a crowded market -A complementary mix of observational studies/modeling to inform trial design and RCT/LSTs should be planned throughout the drug development cycle
- 22. WHAT TYPE OF CER/RE WILL EXTERNAL ENTITIES (E.G., FEDERAL, HTA BODIES, HEALTH PLANS) BE INVESTING IN OR EXPECTING BY 2020 THAT WILL IMPACT THE BUSINESS MODEL FOR DRUG DEVELOPMENT? Federal bodies will invest in methods standards that will help improve quality of observational research; Health plans/HTA bodies will want pragmatic trials that include: 1) active comparators compared to relevant treatment options; 2) in populations of end users; 3) with clinically meaningful endpoints that answers the question, “How does this new drug impact our bottom line?” Health plans and some countries in Europe will be collecting more post-market observational data to better understand this. Drug companies will need to be proactively partnering with health systems, patient and clinician organizations that maintain registries, and state-run registries to enable more efficient, randomized real world trials.
- 23. IN MOVING TO THE NDDP, WHAT ARE THE CHALLENGES FOR INDUSTRY? • Learn to do large, cheap simple trials • Participate in the development of data policies and architecture to support more efficient large simple trials • Understand when payers are aligned about a gap in evidence that needs filling • Determine the product archetype in advance; does it target “too broad” a market (archetype 2) or “too narrow” (archetype 1) based on the developmental decisions/compromises that need to be made • Define the questions that need to be answered at each phase of development – the archetype will help drive an evidentiary strategy • Conduct more exploratory modeling Have more discipline about killing projects and more realism about the target population
- 24. • Barker, R. 2030 - The Future of Medicine: Avoiding a Medical Meltdown (Oxford University Press, New York, 2011). • Barker, R.W. & Garner, S. Adaptive drug development and licensing. Regulatory Rapporteur 9, 13-14 (2012). • Califf, R., Filerman, G., Murray, R. & al. The Clinical Trials Enterprise in the United States: A Call for Disruptive Innovation- Discussion paper (Institute of Medicine, Washington, DC, April 2013). • Chalkidou, K., Tunis, S., Whicher, D., Fowler, R. & Zwarenstein, M. The role for pragmatic randomized controlled trials (pRCTs) in comparative effectiveness research. Clin Trials 9, 436-46 (2012). • Chow, S.C. & Chang, M. Adaptive design methods in clinical trials - a review. Orphanet J Rare Dis 3, 11 (2008). • Messner, D. A., Mohr, P. and Towse, A., 2015. Futurescapes: evidence expectations in the USA for comparative effectiveness research for drugs in 2020. Journal of Comparative Effectiveness Research,(Epub ahead of print). • Messner, D. A., Towse, A., Mohr, P. and Garau, M., 2015. The future of comparative effectiveness and relative efficacy of drugs: an international perspective. Journal of Comparative Effectiveness Research,(Epub ahead of print). • Orloff, J., Pinheiro, J., Levinson, S. & al, e. The future of drug development: advancing clinical trial design. Nature Reviews Drug Discovery 8, 949-957 (2009). • Peto, R., Collins, R. & Gray, R. Large-Scale Randomized Evidence: Large, Simple Trials and Overviews of Trials. Annals of the New York Academy of Sciences 703, 314-340 (1993) • President's Council of Advisors on Science and Technology. Report to the President on Propelling Innovation in Drug Discovery, Development and Evaluation (Office of the President of the United States, Washington, DC, September 2012). • Schneeweiss et al. Clinical pharmacology & Therapeutics 90: 6 December 2011. Assessing the Comparative Effectiveness of Newly Marketed Medications: Methodological Challenges and Implications for Drug Development • Towse, A., Garau, M., Mohr, M.and Messner,D.A., 2015. Futurescapes: expectations in Europe for relative effectiveness evidence for drugs in 2020. Journal of Comparative Effectiveness Research,(Epub ahead of print). REFERENCES
- 25. QUESTIONS TO WORKSHOP PARTICIPANTS • Is it feasible to change drug development in the ways set out? • What barriers to change are there within companies and from regulators and HTA bodies? • Can / should these be overcome? • What happens to drug development costs? Can they come down under any scenario?