Bernard Marr is a world-renowned futurist, board advisor and author of Generative AI in Practice: 100+ Amazing Ways Generative Artificial Intelligence is Changing Business and Society. He has written over 20 best-selling and award-winning books and advises and coaches many of the world’s best-known organisations.
Generative AI based on Large Language Models , the technology behind popular tools like ChatGPT and Google Gemini, is revolutionizing various industries, including the world of drug discovery. By leveraging the power of AI to decode and manipulate the languages of biology and chemistry, pharmaceutical companies are now developing new drugs faster and more cost-effectively. Let’s explore how generative AI is transforming drug discovery, accelerating the development process, and reducing costs.
Generative AI can interpret these languages, aiding in the discovery and development of new drug therapies. By applying LLM-type methods to these biological and chemical languages, AI models can uncover insights previously unobservable, expediting the drug discovery process and significantly cutting costs. Given the high failure rate of new drug therapies – only 10 percent succeed in clinical trials – any technology that enhances efficiency and reduces time and cost is highly valuable.
: The second phase is about generating potential leads – chemicals or proteins that could target the identified disease. The sheer number of possible chemicals and proteins makes this a daunting task. Generative AI can sift through these possibilities and generate novel compounds with the desired properties, creating numerous leads to explore.: In the third phase, the potential drug candidates need to be tested for efficacy. Generative AI can assist in this large-scale screening process.
Generative AI enables pharmaceutical companies to explore potential new drugs with unprecedented scale, speed, and accuracy, facilitating quicker progression to clinical trials., which used AI to develop a drug for idiopathic pulmonary fibrosis, a rare disease that causes progressive lung decline. Traditionally, this process would have taken six years and cost over $400 million. With generative AI, Insilico reduced the cost to one-tenth and the time to two and a half years.
Insilico’s AI was employed at each step of the preclinical drug discovery process: identifying target molecules, generating novel drug candidates, and predicting clinical trial outcomes. Their success extends to developing an AI-generated COVID-19 drug effective against all variants and initiating over 30 other programs targeting various diseases, including cancer.Generative AI’s impact on drug discovery is transformative.
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