Pharmaceutical companies are increasingly outsourcing research activities to academic and private contract research organizations (CROs) as a strategy to stay competitive and flexible in a world of exponentially growing knowledge, increasingly sophisticated technologies and an unstable economic environment.
The R&D tasks that firms choose to outsource include a wide spectrum of activities from basic research to late-stage development: genetic engineering, target validation, assay development, hit exploration and lead optimization (hit candidates-as-a-service), safety and efficacy tests in animal models, and clinical trials involving humans.
According to a recent analytical report by Visiongain, drug discovery outsourcing will continue to grow over the next decade and will rise to a $43.7 billion dollar industry by 2026, as compared to an estimated 19.2 billion in 2016 (or $21.2 billion according to Kalorama Information). This is in line with Vantage’s fresh alliance benchmarking study, revealing that over 80% of bio-pharma respondents report increased alliance activity compared to five years ago. Getting ideas and expertise from external sources is a well-established practice in the pharmaceutical industry with about one-third of all drugs in the pipelines of the top ten pharmaceutical companies initially developed elsewhere, according to a 2014 WSJ article by Jonathan D. Rockoff.
China has been becoming a research powerhouse in many fields of science, but it still is a minor player when it comes to pharmaceuticals. However, recent developments suggest that China’s role in pharmaceutical research may change in the near future.
The first biologics drug, humanized insulin (5.8 kDa), became available in 1982 following the advent of biotechnology, and it marked a new era in pharmaceutical industry. Modern advances in biotechnology permit large-scale syntheses of biologics in a more or less cost-effective manner. Having once started with large peptides and recombinant proteins, biologics nowadays include a wide range of other entities, such as antibodies, monoclonal antibodies, and more recently, nanobodies and related objects, soluble receptors, recombinant DNA, antibody-drug conjugates (ADCs), fusion proteins, immunotherapeutics, and synthetic vaccines.
(Edited version of this post originally appeared in Forbes)
“It is not the strongest of the species that survives, nor the most intelligent, but the one most adaptable to change” -- Leon C. Megginson
Last year brought about new hope and even more hype around the idea of applying artificial intelligence (AI) for “revolutionizing” drug discovery research -- via machines being able to “learn” chemistry and biology from vast amounts of experimental data to propose potent drug candidates, accurately predict their properties and possible toxicity risks. It is supposed to dramatically minimize failures in clinical trials -- saving R&D budgets, time, and most importantly, lives of patients.