{"id":17205,"date":"2022-11-28T17:49:10","date_gmt":"2022-11-28T22:49:10","guid":{"rendered":"https:\/\/d3.harvard.edu\/platform-digit\/?post_type=hck-submission&p=17205"},"modified":"2022-11-28T23:24:18","modified_gmt":"2022-11-29T04:24:18","slug":"insitro-discovery-new-medicines-with-ai","status":"publish","type":"hck-submission","link":"https:\/\/d3.harvard.edu\/platform-digit\/submission\/insitro-discovery-new-medicines-with-ai\/","title":{"rendered":"Insitro: Discovery New Medicines with AI"},"content":{"rendered":"\n\n\n

About Insitro: An AI-Based Drug Discovery Company<\/h2>\n\n\n\t\t
\n\t\t\t
\n\t\t\t\t<\/div>\n\t\t\t<\/figure>\n\t\n\t\t\t\t\t\t\t
\n\t\t\t\t\t
Figure 1. YouTube video describing the power of AI drug discovery in the pharmaceutical industry. (Source: Novartis<\/a>)<\/figcaption>\t\t\t\t<\/figcaption>\n\t\t\t\t\t<\/div>\n\t\t\n\n\n

Insitro <\/strong>is an AI-based drug discovery company headquartered in San Francisco, CA. Founded in 2018, it has made waves in the biotech industry by merging advanced high-throughput biology and cutting edge machine learning. To date, the company has secured over $743M and entered drug discovery and development contracts with the largest global Big Pharma companies – including Gilead and BMS. <\/p>\n\n\n\n

About the AI-Platform Deployment: What is Insitro building and selling?<\/h2>\n\n\n
\n
\"\"<\/a>
Figure 2. Example lock and key analogy illustrating the value AI-based drug discovery platforms in lead drug candidate identification. (Source: Deloitte<\/a>)<\/figcaption><\/figure>\n<\/div>\n\n\n

Insitro is building a new process to drug discovery that is disrupting the way drugs are traditionally discovered. <\/p>\n\n\n\n

Traditionally, as seen at the top of Figure 1, you can imagine that a drug (or “key” in this analogy) acts on a receptor (or “lock”) in the human body to then prompt a therapeutic effect against a person’s disease condition. In the past, drug companies would run drug discovery experiments where they metaphorically would blindly throw hundreds (if not thousands) of possible keys at a lock just to see which ones might fit. <\/p>\n\n\n\n

With the advent of more advanced chemistry and computational methods – particularly machine learning – Insitro has built a more bespoke model. Using large databases of these “locks”, “keys”, and results of those experimental fittings, Insitro can leverage machine learning models to design what the “perfect key” might look like in order to unlock the best therapeutic effect for patients. Based on these designs, Insitro can intelligently design these smart keys and iterate until a final lead drug candidate is identified for in-human clinical trials. <\/p>\n\n\n\n

Insitro’s value creation lies in the speed and cost-savings that it offers to its biopharma clients. Industry experts cite that drug discovery platforms like Insitro’s could reduce preclinical R&D costs by 20-40% and increase the probability of success that a drug candidate successfully makes it to market as a potential $1B\/year blockbuster product. Across the industry, AI drug discovery platforms are projected to drive nearly a 15% increase in annual drug approvals in the United States, raising domestic drug sales from the existing $300B to $340B. <\/p>\n\n\n\n

To-date, with its nearly $750M in funding, Insitro has built both one of the largest drug libraries and databases on drug-target interactions the necessary infrastructure (e.g., complex cell-based human biology models) to continually test these drug candidates on human cells. With both these computational and physical assets, Insitro has positioned itself as one of the leading R&D partners for pharma companies that can deliver cost and time savings. <\/p>\n\n\n\n

Challenges & Opportunities for Insitro<\/h2>\n\n\n\n

Despite the tremendous potential of this field, there are massive challenges for Insitro: <\/p>\n\n\n\n