AI series (part IV): The race is on – using data to transform drug development
Artificial intelligence (AI) applied in conjunction with "big data" has the potential to make drug development more rapid. These new technologies will also lead to the production of sophisticated, personalized medicines. The pharmaceutical industry is already making efforts to speed advances in using AI to develop and test drugs.
One innovation making this possible is the enormous leap that has been made in gene sequencing technology. This, coupled with the algorithms of AI and the analysis of big data, will form the foundation for future cancer therapies and other drugs.
AI is important because it can rapidly analyze effectively masses of health, clinical trial, and genome data. This allows resea#rchers and doctors to use it, for example, to pinpoint abnormalities and help to determine suitable immune response targets.
BioNTech, of Mainz, for example, is using AI as it works in partnership with a number of companies, including Genentech and Genmab, and the pharmaceutical giants, Ely Lilly &Co., Sanofi, Pfizer, and Bayer Animal Health. One of BioNTech's specialties is developing vaccines that stimulate a patient's immune system to attack cancer cells. GEN Genetic Engineering & Biotechnology News recently placed BioNTech at number one in its ranking of the world's top ten immuno-oncology startups.
Other companies are taking a different AI approach. Molecular Health in Heidelberg has spent over a decade setting up a data bank containing clinical trials results, as well as data on effective ingredients and genetics. Molecular Health's CEO, Friedrich von Bohlen, says the company's system is better able to predict a clinical trial's probability of success than any other procedure, meaning Molecular Health has the capability to save drug companies time and money.
The Darmstadt-based multi-national pharmaceutical company Merck, meanwhile, has set up a joint venture, Syntropy, together with the US software company Palantir. One of its aims is to gather vast amounts of earlier pharmaceutical trial data from companies and research institutes and make them more available for sharing and input into drug development.
The online publication BiopharmaTrend.com reports that using AI to speed the drug discovery process is currently a "mini-trend." The article says millions of dollars in venture capital is currently pouring into this area, while at the same time, drug makers are hunting for external AI partnerships.