Pharma R&D Today
Ideas and Insight supporting all stages of Drug Discovery & Development
Snakes (aka Chutes) and Ladders – failures and opportunities
Posted on October 13th, 2017 by Dr Andrew A. Parsons in Pharma R&D
If there ever was a children’s game that would help prepare the next generation of pharmaceutical R&D scientists and researchers, it would be Snakes and Ladders (Chutes and Ladders in the US).According to Wikipedia, there is quite a history in its development as a worldwide game with roots in personal development and life learning (1). It was a game that showed there are plenty of things to hold us back from salvation.
The recent news of yet another failure in clinical development for dementia is disappointing for everyone involved and those hoping for success (2). We have slipped down the board yet again in our quest for a new treatment. For experts in the field, the process of trial and error is a trusted way to create better and better questions and broaden our understanding of physiological systems. Learnings appear to be emerging from looking at the recent failures of other approaches to Alzheimer’s Disease (3).
As scientists, we often focus on the technical issues involved in the data not coming out as expected. I know from my time in stroke research that the impetus to address issues in translation of preclinical to clinical data can result in the development of consensus statements with an aim to ensure quality and reproducibility of preclinical studies (4,5). These STAIR criteria highlight the importance of scientific discipline and experimental design (e.g. sample size calculations, the blinding of studies, ensuring reproducibility) which are clearly issues across the life sciences (6). The STAIR criteria also highlight the need for more (and even more) data and ways for reporting potential conflict of interests. However, they failed to address the diminishing appetite for investors, senior managers and developers to spend the huge amounts of money required to get to a successful product launch. Consequently, research and clinical development strategy moved into different directions.
With so many clinical trials across a range of drug modalities and biological mechanisms of action for Alzheimer’s Disease not demonstrating difference from placebo treatments, is there a risk that this may happen in neurogeneration? In my opinion, this is a qualified yes. With the current focus on the social and humanitarian impacts of dementia, there will be continued interest in finding new treatments. However, there will be a limit to investment and interest in the area. I see (at least) two significant challenges.
The first will be how to select the best candidates to go forward into clinical development. The second, once agents are in development, will be how to align decision-making and the complex expectations of a variety of stakeholders to coming to agreement on serial, transparent and accurate Go/No-Go decisions. Ultimately, the second priority is about decision-making so that, following sequential trials, a clear decision on the validity of initially the agent, and then the biological target, can be made in regard to their effect in the disease process.
For the first priority, candidate selection, “less is more” is the approach I suggest. There is a tendency that scientists want to conduct more and more experiments to act as gate keepers to progression (see 5). We absolutely need to ensure scalability of manufacturing process, safety, tolerability and their developability at this stage. As an industry, we have made great progress in these areas. Where we still struggle is in translation of biological activity into clinical relevance. If we start with the end in mind, there are two key questions at this stage: How can we work back from the clinical development population(s) with relevant preclinical experimental designs? And, is there a strong evidence-based hypothesis that is supported by data? This moves our strategy to a bespoke scientific-led inquiry and away from satisfying a “hit” in a gold standard preclinical model of dubious clinically predictive qualities.
The second priority touches on the human factor. It is more than potential conflicts of interest. These are perhaps difficult to define in the complexity of the interfaces between academia, investors, development organizations and regulators. However, falling short of conflicts, there will be competing priorities and trade-offs that need to be made that will influence decision-making at all key stages of progression. Finding ways to describe what these are and different ways to incentivize individuals and organizations across private, public and charitable sectors will be key. Coming back to key scientific principles, we not only need to ensure appropriate experimental processes are incorporated into every activity – there should also be clarity on whether the experiment will be able to falsify the hypothesis. After all, we can only disprove a hypothesis in a scientific context. This is perhaps one place to start to build alignment across interested parties.
I think one thing is certain. To bring the medicines that society needs to treat the growing issue of dementia, we need to move from the snakes and find the ladders.
- Fisher, M (1999). Stroke 30: 2752 – 2758
- Fisher, M. et al., (2009). Stoke 40: 2244-2250.
- Collins, F.S. & Tabak, L.A. (2014). Nature 505 (7485) 612
All opinions shared in this post are the author’s own.
R&D Solutions for Pharma & Life SciencesWe're happy to discuss your needs and show you how Elsevier's Solution can help.
Dr Andrew A. Parsons
Director of Reciprocal Minds Limited & Chairman of Pharmasum Therapeutics AS
- Harnessing big data — it’s challenging, but it can be done
- Pharma’s Path to Adopting AI and Other Emerging Technologies
- Drug Development Insights from the 36th Annual J.P. Morgan Healthcare Conference
- Translational Medicine, Data Access and Pharmaceutical Innovation
- Unifying Data Standards to Promote Innovation