Net present value approaches for drug discovery

Improving target assessment in biomedical research: the GOT-IT recommendations

Academic research plays a key role in identifying new drug targets, including understanding target biology and links between targets and disease states. To lead to new drugs, however, research must progress from purely academic exploration to the initiation of efforts to identify and test a drug candidate in clinical trials, which are typically conducted by the biopharma industry. This transition can be facilitated by a timely focus on target assessment aspects such as target-related safety issues, druggability and assayability, as well as the potential for target modulation to achieve differentiation from established therapies. Here, we present recommendations from the GOT-IT working group, which have been designed to support academic scientists and funders of translational research in identifying and prioritizing target assessment activities and in defining a critical path to reach scientific goals as well as goals related to licensing, partnering with industry or initiating clinical development programmes. Based on sets of guiding questions for different areas of target assessment, the GOT-IT framework is intended to stimulate academic scientists' awareness of factors that make translational research more robust and efficient, and to facilitate academia-industry collaboration.

Future unmet medical need as a guiding principle for pharmaceutical R&D

In pharmaceutical R&D the strategic focus is on addressing areas of high unmet medical need. 'Unmet medical need' is a widely used term in the healthcare sector but a common definition does not exist. The current standard of care determines the current unmet medical need, whereas the future unmet medical need (i.e., the unmet medical need when a new product reaches the market) and the extent to which the unmet need is addressed by the new product significantly impact its value. We have defined six dimensions as key drivers of (future) unmet medical needs of patients in a given setting. In the absence of quantifiable criteria, structured expert assessment techniques, such as the Delphi method, can guide portfolio strategies, especially for early-stage assets.

The price of innovation - the role of drug pricing in financing pharmaceutical innovation. A conceptual framework

The debate on drug prices has reached new heights with the controversy around the role of prices in promoting innovation. Critics claim that prices of innovative drugs are excessive and argue that lowering prices will not harm the flourishing innovation. On the opposite end, the pharmaceutical industry insists that restrictive pricing policies will have a detrimental impact on their ability to generate innovation. Amid these two divergent positions, this manuscript presents a conceptual framework to better understand the role played by drug prices to influence the ability of pharmaceutical firms to raise money in capital markets and hence finance pharmaceutical innovation. We argue that deviations from established value-based pricing principles, by either firms or payers, will distort access by firms to capital and lead to an undesirable level of innovation in the long term. We hope that this framework helps policy-makers anticipate the impact of their proposals, and ultimately guide policies towards setting optimal drug prices as a means to maximise social welfare.

Integrating dose estimation into a decision-making framework for model-based drug development

Model-informed drug discovery and development offers the promise of more efficient clinical development, with increased productivity and reduced cost through scientific decision making and risk management. Go/no-go development decisions in the pharmaceutical industry are often driven by effect size estimates, with the goal of meeting commercially generated target profiles. Sufficient efficacy is critical for eventual success, but the decision to advance development phase is also dependent on adequate knowledge of appropriate dose and dose-response. Doses which are too high or low pose risk of clinical or commercial failure. This paper addresses this issue and continues the evolution of formal decision frameworks in drug development. Here, we consider the integration of both efficacy and dose-response estimation accuracy into the go/no-go decision process, using a model-based approach. Using prespecified target and lower reference values associated with both efficacy and dose accuracy, we build a decision framework to more completely characterize development risk. Given the limited knowledge of dose response in early development, our approach incorporates a set of dose-response models and uses model averaging. The approach and its operating characteristics are illustrated through simulation. Finally, we demonstrate the decision approach on a post hoc analysis of the phase 2 data for naloxegol (a drug approved for opioid-induced constipation).

Risk of discontinuation of Advanced Therapy Medicinal Products clinical trials

OBJECTIVE

Advanced therapy medicinal products (ATMPs) constitute a class of innovative products that encompasses gene therapy, somatic cell therapy, and tissue-engineered products (TEP). There is an increased investment of commercial and non-commercial sponsors in this field and a growing number of ATMPs randomized clinical trials (RCT) and patients enrolled in such trials. RCT generate data to prove the efficacy of a new therapy, but the discontinuation of RCTs wastes scarce resources. Our objective is to identify the number and characteristics of discontinued ATMPs trials in order to evaluate the rate of discontinuation.

METHODS

We searched for ATMPs trials conducted between 1999 to June 2015 using three databases, which are Clinicaltrials.gov, the International Clinical Trials Registry Platform (ICTRP), and the EU Drug Regulating Authorities Clinical Trials (EudraCT). We selected the ATMPs trials after elimination of the duplicates. We identified the disease areas and the sponsors as commercial or non-commercial organizations. We classified ATMPs by type and trial status, that is, ongoing, completed, terminated, discontinued, and prematurely ended. Then, we calculated the rate of discontinuation.

RESULTS

Between 1999 and June 2015, 143 withdrawn, terminated, or prematurely ended ATMPs clinical trials were identified. Between 1999 and June 2013, 474 ongoing and completed clinical trials were identified. Therefore, the rate of discontinuation of ATMPs trials is 23.18%, similar to that for non-ATMPs drugs in development. The probability of discontinuation is, respectively, 27.35, 16.28, and 16.34% for cell therapies, gene therapies, and TEP. The highest discontinuation rate is for oncology (43%), followed by cardiology (19.2%). It is almost the same for commercial and non-commercial sponsors; therefore, the discontinuation reason may not be financially driven.

CONCLUSION

No failure risk rate per development phase is available for ATMPs. The discontinuation rate may prove helpful when assessing the expected net present value to support portfolio arbitration and may be considered by patients and potential investigators in their decisions to participate in ATMP trials. These results carry limitation because the rationale for discontinuation is unknown. Further research about the reasons of discontinuation and the risk of negative results is needed to inform stakeholders.

Open source drug discovery - a limited tutorial

Open science is a new concept for the practice of experimental laboratory-based research, such as drug discovery. The authors have recently gained experience in how to run such projects and here describe some straightforward steps others may wish to take towards more openness in their own research programmes. Existing and inexpensive online tools can solve many challenges, while some psychological barriers to the free sharing of all data and ideas are more substantial.