It’s estimated that, on average, to bring one new drug to the market can take 1,000 people, 12-15 years, and up to $1.6 billion. Pharmaceutical companies are grappling with these scandalous costs and constantly in search for inefficiencies in the drug discovery process, and hope to fasten the process by focusing on key elements, like management models, new technologies and creative study approaches. With many new viruses and bacteria daunting the globe there is an increased necessity to innovate and develop new drugs and safeguard public health. Also with patent cliff looming large, pharma companies need to evolve their R&D efforts to ensure that the core of their business keeps pace with the changes. With increasing competition, experts are looking at newer methods to speed up and increase accuracy rates. One such approach is using Artificial intelligence in drug discovery.
The technology aims to streamline the initial phase of drug discovery, which involves analyzing how different molecules interact with one another—specifically, scientists need to determine which molecules will bind together and how strongly. They use trial and error and process of elimination to analyze tens of thousands of compounds, both natural and synthetic. "Many large pharma companies are starting to realise the potential of this approach and how it can help improve efficiencies," said Mr Andrew Hopkins, chief executive of Scotland-based Exscientia, which announced the new tie-up with GSK. Mr Hopkins, who used to work at Pfizer, said Exscientia’s AI system could deliver drug candidates in roughly one-quarter of the time and at one-quarter of the cost of traditional approaches.
Exscientia also signed a 250 mn Euros deal with Sanofi in May. As part of this agreement, Exscientia will be responsible for all compound design, whilst chemistry synthesis will be delivered by Sanofi. With its unique AI platform, Exscientia is delivering a pipeline of efficacious, bispecific small molecules, as well as highly selective single target candidates, for multiple indications.
In an interaction with Mr Andrew Hopkins, CEO, Exscientia. Please check below for Excerpts:
What is artificial intelligence (AI) and how does it speed up drug discovery process?
AI, if used correctly, is a new approach to drug discovery, that uses computer algorithms to search create original solutions to the questions a drug discovery scientist might ask when designing a new medicine. These systems are uniquely able to learn from existing data resources, much in the way that a human would learn and then apply the knowledge gained on a new project. However the amount of data now available is so vast that it is beyond a human’s capability. For AI focused towards drug design, where Exscientia focuses its expertise, the typical sources of information could be the vast resources of chemical structure, pharmacology, bioassays data as well as other supporting literature and patent information. The AI algorithms then apply the distillation to the design of new small molecules. Successful molecules will hit the desired target whilst at the same time avoiding known selectivity, toxicology or pharmokinetic issues (among many other parameters). Further refinement can lead to completely new and optimized molecules (and IP) for advancing towards the clinic. AI is also being applied to many areas of drug development. For example AI approaches might look at better patient stratification for clinical trials, thereby fitting the patient to the treatment being tested better, enabling quicker recruitment and increasing the likelihood of getting the required clinical response for regulatory approval.
- What are the key trends that will drive the growth of AI in drug discovery for the next 5 years?
The need to reduce R&D costs is a major drive. Lead optimisation is the highest cost per launched drug due to the number of projects researched that never reach the market. Improving discovery efficiency through high quality candidates that are discovered effectively would dramatically improve these metrics. Exscientia's deal with GSK is looking at this exact problem, designing candidates in a highly productive manner.
Also, the need to reduce healthcare costs – combination therapies (e...Read More
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