Generative AI transforming big pharma drug design

Generative AI is transforming the expensive and slow process of drug design and offers the opportunity for the discovery of novel drug compounds.

As Generative AI (GenAI) begins to transform the pharmaceutical industry, another pharma giant, Seoul-based company Daewoong Pharmaceutical, this week unveiled its AI-driven drug development system. DAVID (Daewoong Advanced Virtual Database) is an 800 million-compound database composed of recently discovered compounds and research on those compounds developed over the past 40 years. Daewoong stated that it believes there are one billion potential new drug candidates in the database.

The cost and time taken for drug discovery is increasing

According to a report from Deloitte, the top 20 global pharmaceutical companies collectively spent $139 billion on R&D in 2022, down two per cent from 2021. However, the length of time taken for drug development went up from 6.9 years to 7.1 years in the same period, which means the average cost of developing a new drug rose by $298 million to $2.3 billion in 2022.

It is also estimated that only 1 in 10,000 potential drug candidates reaches approval. GenAI, however, is set to transform drug discovery and development and is predicted to halve development times while significantly streamlining the search for potential new drugs. According to BCC Research, the global market for AI-based drug discovery and design is estimated to increase from $1.6 billion in 2023 to $5.7 billion by 2028 – a CAGR of 29.6% over the period^[1].

Daewoong, for example, built DAVID and developed AIVS (AI-based Virtual Screening) to uncover active substances that target specific proteins. Using generative AI, it can quickly discover new patentable active substances and perform 3D modelling. From DAVID and AIVS, the company has developed DAISY (Daewoong AI System), a web-based system that allows researchers to discover potential new compounds and quickly predict their properties.

New generation of AI-based drug design and discovery platforms

Using DAISY, Daewoong has already discovered an active substance that reacts to two target proteins related to weight loss and the treatment of diabetes, and within six months uncovered an effective active substance for cancer cell inhibition.

However, it’s not the first. In June 2023 Shanghai-based Insilico Medicine claimed that it had discovered the world's first small molecule drug candidate – INS018_055 for the treatment of the degenerative lung disease idiopathic pulmonary fibrosis (IPF) – developed by GenAI. It also claimed it was the first AI-designed drug to reach the clinical stage.

Likewise, in 2023, pharma giants including Boehringer Ingelheim, AstraZeneca, and Pfizer all announced partnerships that will harness the power of GenAI for drug design and discovery.

Meanwhile, on 7 January Isomorphic Labs – a drug discovery spinout from Google’s US-UK AI collaboration, DeepMind – announced two new partnerships with Novartis and Eli Lilly, with the aim of reducing the discovery stage from an average of five years to two.

Global AI-based drug discovery partnerships on the rise

Under the deal with Eli Lilly, Isomorphic Labs will receive $45 million upfront to collaborate on research into small molecule therapeutics against multiple targets, while it is reported to have received an upfront payment of $37.5 million from Novartis to discover small molecule therapeutics against three undisclosed targets.

Eli Lilly already has a partnership with Shenzhen-based Xtalpi – a Tencent-backed AI drug discovery startup – after signing a deal worth up to $250 million to unearth potential medicines for an undisclosed disease.

The collaboration aims to discover drug candidates for a disease that currently has no medicine available. The aim is that the Xtalpi platform uncovers novel drug compounds, which Eli Lilly can then commercialize.

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^[1] https://www.bccresearch.com/market-research/healthcare/ai-in-drug-discovery-market.html