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August 2015

Game-changers in drug development: the technologies that are revolutionizing research

7. august 2015 at 20:15 | Veronika Valdova |  Medicine & Pharmacy

Advancements that occurred in medicine since the WW2 were possible due to establishment of formal process of drug discovery and testing in animal and human trials. The drug discovery, development and commercialization industry relies on a set of methodologies and techniques anchored in national legislation and international guidelines to make sure the medicines brought to market are effective and safe in the context of conditions for which they are being used.

As a result of all these obligations and safeguards the process of introduction of new medicines is a very expensive, lengthy and risky one. Merely a decade ago, in 2004, the cost of launch of a successful drug was about $1 billion. According to William Bains (Drug Discovery World, 2004) development of a new drug took 12.5 years on average. Much of the blame for the high costs has been traditionally laid on medical and technical failures. But Bains, unlike many his contemporaries, argues that high cost of drug development shall be attributed to other factors than just technical failures, and blames organizational indecisiveness and endless recycling of projects instead. His main argument is that the definition of success within the context of drug development and big pharma environment is progression of the project to the next stage, and that the key to reduction of excess costs is the reduction of repeats at Phase III of human trials.

Ten years later the Tufts center for the study of drug development (R&D Cost Study Briefing, 2014) estimated that the average pre-tax industry cost per new prescription drug approval, inclusive of failures and capital costs, is $2.6 billion: 2.5-fold increase since 2004. Tufts university team included in their study 1,442 compounds first tested in humans anywhere in the world in the period from 1995 to 2007. For this set of compounds, 7.1% were approved, 80.3% had been dropped, and 12.6% were still active in some phase of human clinical studies. Whilst the cost of pre-human research remained more or less the same, the cost of human phase trials increased significantly. The out-of-pocket cost per approved new compound grew steadily whilst approval success rate declined.

Hay and colleagues (Nature Biotechnology, 2014) analyzed 4,451 drugs with 7,372 independent clinical development paths for survival of drug candidates by therapeutic area, molecule type, and by indication. The greatest compound attrition, 68%, was unsurprisingly in phase 2 during first tests in people with the target disease. Additionally, only about 60% drug candidates advance from large scale phase 3 trials to regulatory filing. LaMattina (Forbes, 2014) used this analysis to support his vision that phase 1 (first-in-man) studies should lead to 85-90% compound survival, and the way forward are precompetitive public-private initiatives similar to Accelerating Medicines Partnership (AMP).

One possible answer to the low success rate of phase 1 and 2 studies may be the low reproducibility rates within life science research that according to Freedman (PLOS Biology, 2015) undermine cumulative knowledge production and contribute to both delays and costs of drug development. Freedman's estimates that about 50% pre-clinical studies conducted in the U.S. alone cannot be reproduced due to incorrectly chosen biological reagents and reference materials (36.1%), inappropriate study design (27.6%), flaws in data analysis and reporting (25.5%), and inadequate laboratory protocols (10.8%). The total cost burden of irreproducible preclinical research is then placed at $28.2 bn.

But there are ways of improving the odds of success within the drug development enterprise. The enabling and potentially game-changing technologies include advances in pharmacogenomics, big data visualization techniques, and the advanced in-vitro testing technologies. As these breakthrough technologies mature they are slowly but surely transforming the industry.

Ahn (Genomics & Informatics, 2007) argues that pharmacogenomics, a study on the impact of human genetic variations on individual response to drugs, has the potential to revolutionize the practice of medicine. Utilization of knowledge of individual genetic makeup would predict individual response to drugs and likelihood of serious toxicity. According to Ahn, the era of "one-size-fits-all" type of blockbuster medicines is coming to an end, to give way to personalized medicine. In drug development, genomic tests enable better evauation of molecular targets specific to cancer cells. In medical practice, screening for CYP450 gene variations allows selection of the most appropriate treatments for patients with mutations in CYP2D6 and CYP2C19 genes.

Advanced analytical techniques are transforming drug discovery, development and commercialization by providing near-instant visualization of studied events. Challenges of data management in healthcare are overwhelming not only due to its total volume but also due to its diversity. Analytics of social media helps to evaluate perception and feedback; electronic data capture is making data processing substantially faster and cheaper; and specialized analytical platforms allow monitoring of clinical trial performance indicators in near-real time. Big data platforms help avoid potentially costly issues such as adverse events, delays and repeats, and enable effective communication between functions, stakeholders and partners. Evaluation of safety and efficacy profile of new drug can now be performed in real-life conditions, taking pharmacovigilance to completely different level. Big data platforms are accelerating healthcare the same way as radar and night vision transformed warfare: with big data the invisible now becomes visible, detectable and actionable.

The third transformation enabler in drug development is Wyss Institute's project Human-on-a-chip. These microfluidic cell culture devices simulate organ-level human physiology including multicellular architectures, tissue-tissue interfaces, physicochemical environments, and vascular perfusion, and create real-time in-vitro analysis of drug candidates, valuable especially for the study of molecular mechanisms of action, prioritization and selection of leads, toxicity testing and biomarker identification.

Overall, the current apparent crisis in drug development and success rate of new drugs seems to be coming to an end due to breakthrough technologies that all together in combination have the potential to substantially transform the drug development process - for the benefit of the patients.