The drug development lifecycle is long and fraught with heavy risk -- it takes a staggering 10 – 15 years on average, with ultimately only 12 percent of drugs in clinical trials gaining approval by the U.S. Food and Drug Administration (FDA) . To put this in perspective, 22.7 percent of all global research and development spending in 2017 was in the healthcare industry, second only to 23.1 percent spent in the computing and electronics industry, yet the product lifecycle is longer, and costs are much higher . For example, the original iPhone took two and a half years to develop from concept to launch, and an estimated $150 million spent in research and development . In contrast, the average cost of new drug and biologics is $2.87 billion when factoring in the post-approval research and development costs, according to figures released in May 2016 by The Tufts Center for the Study of Drug development (CSDD) . For pharmaceutical companies that have launched more than four drugs, the median cost is closer to a staggering $5.3 billion according to analysis by industry expert Matthew Herper of Forbes .
Deep Knowledge Ventures (DKV) is a Hong Kong based investment fund with teams in London, Geneva, and San Francisco. The fund primarily invests in DeepTech, AI, and advanced biomedicine. In 2015, DKV incorporated a subsidiary investment fund Deep Knowledge Life Sciences (DKLS), a London-based venture fund, focused on disruptive biopharmaceutical, medical device, and healthcare companies in a partnership with scientists at the universities of Oxford and Cambridge. DKLS it has been the lead investor so far in a number of promising biomedicine and longevity companies: Insilico Medicine (and the consortium of companies around Insilico Medicine, including Youth Laboratories and Longenesis) and other companies in the fields of Geroscience, NeuroTech, Preventive Medicine, AgeTech and Longevity. The Pharma Division of Deep Knowledge Analytics is the leading analytical entity of DKLS specifically focused on deep intelligence of the pharma industry and the AI for Drug Discovery sector.
Theoretically, the process of drug development is a compact five-step process. However, in reality, it takes an average of 12 years, costing companies more than a billion dollars for a drug to travel from the laboratory to a pharmacy. This long, complex, and expensive journey is challenging but it offers an opportunity to bring in an impactful change. This is why more and more pharmaceutical companies are exploring advanced technologies such as artificial intelligence, machine learning, big data and cloud computing to streamline the process of drug discovery to drastically reduce both time and costs. Drug discovery and development is the first step of the five-step process for drug development established by the FDA.
The healthcare industry is not immune to software and technological advancements. In fact, the use of emerging technologies like artificial intelligence (AI) has gradually begun to revolutionize research activities in the industry. Major advances in science and technology are also likely to improve diagnosis and treatment in the future. The pharma/biotech industry has started adopting artificial intelligence, the simulation of human intelligence processes by machines, especially computer systems, albeit slowly. It is touted as the next big emerging technology in the biotech industry as it can drastically reduce time and costs involved in developing life-saving drugs.
The top 10 pharma companies have all collaborated with or acquired AI technologies: Novartis, Roche, Pfizer, Merck, AstraZeneca, GSK, Sanofi, Abbvie, Bristol-Myers Squibb, and Johnson & Johnson. Reports projecting where the industry would be in terms of artificial intelligence (AI) in 2020 predicted that AI and machine learning were set to transform the pharmaceutical industry … in the near future. Rock Health has monitored investments within the digital health ecosphere since 2011, and it reports that investments have started to shift into the pharmaceutical arena, mostly within the categories of R&D, clinical trials, and digital therapeutics, which includes using AI. According to a 2017 report by Pharma IQ, 95% of the pharma professionals surveyed expected the impact of intelligent enterprise technologies to take hold in the wider drug development industry over the next three years, with one-fifth of the respondents believing that the industry was on the cusp of a revolution. The cusp is here now and will continue to grow into 2020.