Artificial intelligence is all set to permeate various sectors of life science, including the pharmaceutical and biotech industry. The lifecycle of developing a new drug of stimulant is an extremely risky, long and laborious process that takes longer 10-15 years of time, and only 12% of the drugs registered for clinical trials manage to win the approval of the US Food and Drug Administration (FDA) authorities.
In simpler words, in 2017 alone, around 22.7% of all the global spending on research and development was allocated to the healthcare industry, which falls second after the 23.1% spending on research within the computers and electronics industry. And yet, the product lifecycles and developmental expenditures are much greater across the healthcare industry.
For instance, it took the original iPhone model two and a half years to be developed, from the concept phase to its ultimate launch, around $150 million was spent on its research and development. On the other hand, the average expenditures undertaken to research and develop a new medicine, biologics or drug is around $2.87 billion after taking into account the post-approval costs of research and development.
Pharmaceutical organizations and business that work on introducing more than four drugs and medical products end up paying the staggering costs of over $5.3 billion. The advent of artificial intelligence in the pharmaceutical research and development can help businesses reduce both, the cost and time that it takes to research and develop new drugs and medical treatments.
Forward-thinking Venture Capital Companies & AI Startups in Life Sciences
A variety of future-strategizing venture capital organizations and investments have emerged to welcome the advent of artificial intelligence and revolutionize the process of life sciences. Majority of the upcoming artificial intelligence ventures in the biotech and pharmaceutical industry are currently in the phase of discovering and identifying new drugs.
It is evident that the advent of artificial intelligence can help cut down the time that is required to identify and develop new drugs, which will bring about incredible real cost savings. Artificial intelligence is being employing in drug research, discovery and development in a wide variety of techniques.
Let’s take a look at some:
- Scoring synthetic complexity
- Organic synthesis and designing
- Automating the molecule design
- Computer-powered synthesis
- Computer-aided retro-synthesis matched with molecular comparisons
- Examining the potential of drug performance while conducting trials
- Identify the off-label benefits
- Designing personalized drugs and treatments
- Analyzing the toxic potential before conducting clinical trials
Atomwise is a startup that involves the use of patented structural convolutional neural networks to examine the potential of binding proteins with tiny molecules, and increasing the process of drug discovery and developments. The AtomNet solution allows researchers and drug developers to examine more than 20 billion chemical compounds every single day, cutting down the years and years of time that was earlier required to discover and design the process of drug optimization. Founded by Y Combinator, Dolby Family Ventures, OS Fund, Tencent Holdings and Khosla Ventures amongst other investors, Atomwise is a remarkable new platform in Life Sciences.
TwoXar, a biopharmaceutical firm in Palo Alto, is funded by Andreessen Horowitz Bio Fund, OS Fund, Standford-StartX fund, Softbank Ventures and the CLI Ventures, and it offers a remarkable drug discovery solution powered by artificial intelligence. This drug discovery platform allows discovery during vivo testing with the help of its iconic predictive technology.
Insilico Medicine, is another artificial intelligence startup that was established by Alex Zhavoronkox in 2014, and funded by Bold Capital, WuXi appTec, Pavillion Capital and others. It employs generative adversarial networks (GANs) to initiate new molecule drug discovery, develop biomarkers, and conduct research on aging.
BenevolentAI, a London-based startup, uses artificial intelligence to streamline the entire process of drug discovery along with the phases of research and development. Various investors, including Woodford Investment Management and family offices has invested $200 million into this startup. It’s groundbreaking new discovery is a Parkinson’s drug, which is currently in Phase 2B clinical trials, along with an ALS drug that is expected to begin clinical trials within five years.
Artificial Intelligence Ventures by Global Pharmaceutical MNCs
According to the pharmaceutical company rankings 2017 given by FiercePharma, the top 15 giants include Johnson & Johnson, Roche, Pfizer, Novartis, Sanofi, Merck & Co., GlaxoSmithKline, Bayer, AbbVie, Gilead Sciences, Eli Lilly, Amgen, AstraZeneca, Teva, and Bristol-Meyers Squibb.
Let’s take a look at how the top 3 pharmaceutical giants are using artificial intelligence to develop innovative new treatments and drugs for the future:
1. Johnson & Johnson ($76 Billion)
The Life Sciences department run by Johnson & Johnson has established JLABS, an incubator powered with several AI startups, including WinterLight Labs, A2A Pharmaceuticals, Fited, Analytics 4 Life, Envisagenics, Human Microbiology Institute and Savor Health.
2. Roche ($54 Billion)
Genentech, a subsidiary of Roche, has revealed a new collaboration with GNS Healthcare, a Precision Medicine company venture, to identify and test new oncology medicines and response markers amongst patients.
3. Pfizer ($53 Billion)
Pfizer announced a collaboration with IBM Watson Health for Drug Disc0very, and their project is centered on drug discovery to provide immune-oncological research and medicinal development assistance. IBM Watson Health for Drug Discovery is powered with an Artificial Intelligence solution that provides research from four million patients, more than a million full-text articles from acclaimed and regularly updated medical journals, and 25 million Medline abstracts.
Pfizer is currently undergoing another collaboration with XtalPi, which is funded by Google, Tencent and Sequoia China, in a project to put together artificial intelligence-powered machine-like learning skills with the mechanisms of quantum physics to examine and identify the pharmaceutical compounds and features of molecules to make drug discovery, research and development more efficient and easier.
The leading academic institutions and research centers of the world are currently engaged in developing groundbreaking artificial intelligence solutions and platforms for drug discovery. A research team from Stanford has put forward a one-short learning drug discovery technique that is capable of bringing about remarkable reductions in the time durations required to discover and develop new medications.
Earlier in 2018, the MIT development the Machine Learning for Pharmaceutical Discovery and Synthesis consortium in collaboration with various partners from the pharmaceutical industry, including Novartis, Pfizer, Bayer, WuXi, Amgen, and Lilly amongst others.
Artificial intelligence is all set to revolutionize the pharmaceutical and biotech developments, and in the US alone, biopharmaceutical business have spent over $75 billion a year in undertaking research and development on new drug discoveries. Artificial intelligence startups and collaborations within the industries and academic research centers are increasingly giving birth to new artificial intelligence solutions that focus on reducing the time duration to develop new drugs, providing competitive advantages to the pharmaceutical giants, and forward-thinking developments that promote viability.
- PhRMA. “2017 Biopharmaceutical Industry Profile.” Accessed July 4, 2018. http://phrma-docs.phrma.org/industryprofile/pdfs/2017IndustryProfile_Brochure.pdf.
- Statista. “Percentage of global research and development spending in 2017, by industry.” Accessed July 4, 2018. https://www.statista.com/statistics/270233/percentage-of-global-rundd-spending-by-industry/
- Nieto-Rodriguez, Antonio. “Is the iPhone the best project in history?” CIO. Nov 3, 2017.