Next-Gen Technologies The Impact of Generative AI & AI Solutions on Drug Discovery
Pharma companies are looking for new technologies to speed up the drug discovery process. For this purpose, industry players are exploring generative artificial intelligence as well as many other innovative AI solutions to optimize their results and deliver faster solutions to the market. Researchers are also keen to merge generative AI platforms like ChatGPT with other existing AI solutions to gain positive results.
Prompt and let ChatGPT type everything for you, let it come up with interesting ideas for a wide range of topics so that one’s precious time is saved and work is carried out more efficiently. This is the most generic notion around ChatGPT but what is this technology all about?
What is ChatGPT?
ChatGPT (Generative Pre-Trained Transformer) is an Artificial Intelligence (AI) based chatbot that has the capability to understand and answer complex questions in the form of human-like conversations. Developed by the US firm OpenAI, the platform is an example of generative AI i.e. it has the ability to identify different patterns and structures in an existing data set to produce new text based on the user’s prompts. This has got researchers from the pharma sector excited as it can identify potential drug targets, predict properties of new compounds and also improve clinical trials.
Applications of Generative AI
Let’s delve deeper into this, identifying new drug targets plays an important part in the drug discovery process. For this, researchers usually have to read numerous scientific literature articles to find relevant information which takes up a lot of their time. Not only this, after all the reading, there is also a high chance of committing errors or missing out on valuable information. This is where generative AI platforms like ChatGPT comes in.
The AI-backed model can browse through and analyze a number of literature articles in a short span of time and also help researchers to identify potential new drug targets. It can also be utilized to identify patterns and trends from huge data sets such as clinical trials.
An example of this is the collaboration between the University of Oxford and the technology pioneer IBM. The partners made use of generative AI, which was fed with raw data, to deliver four new potential Covid-19 antiviral drugs.
ChatGPT also has the potential to communicate with other existing AI solutions and deliver output in the form of simple text which will help experts in the field. Although, this is currently at a nascent stage but many big-ticket players are already experimenting with this new platform.
Artificial Intelligence on the Rise
While the sector experiments with generative AI, research institutes as well as pharma players are also teaming up with innovative AI solution providers to accelerate their drug discovery process in the meantime. For instance, Helix Group, a Stanford University-based research lab partnered with BenevolentAI, a leading clinical-stage AI-drug discovery company, to discover more effective methods to extract knowledge from biological and clinical information and ultimately extend the potential of artificial intelligence in helping scientists discover and develop better medicines, mentions a press release by BenevolentAI.
Another example of AI: A team of researchers from the National University of Singapore (NUS) collaborated with clinicians from the National University Cancer Institute, Singapore (NCIS) which is part of the National University Health System (NUHS), to use an AI tool which helped doctors to make optimal and personalized doses of chemotherapy for patients.
With respect to pharma companies, recently, the US-based pharma company Eli Lilly and Company joined hands with the prominent pharmaceutical technology firm XtalPi for drug discovery. This partnership will make use of XtalPi's integrated AI capabilities and robotics platform (AI + robotics drug R&D platform) to deliver a novel compound to Eli Lilly which can then be used for clinical and commercial development. With this collaboration, the pharma firm aims to automate its research and achieve better results, mentions a release by XtalPi.
Astrazeneca which became popular among the general public during the global Covid-19 pandemic has also adopted AI and machine learning to accelerate the drug discovery process. The pharma major has teamed up with BenevolentAI, an AI-enabled drug discovery and development company to discover potential new drugs for chronic kidney disease and idiopathic pulmonary fibrosis. According to BenevolentAI’s recent press release, Astrazeneca presented new preclinical data on an AI-generated target. It also added that the research provides further scientific information on Serum Response Factor as a potential target for idiopathic pulmonary fibrosis.
Next, the pharma giant Pfizer has entered into an agreement with Cytoreason, a leading technology company developing computational disease models. Under this partnership, Pfizer makes use of Cytoreason’s artificial intelligence technology for drug development. Cytoreason’s biological models are being adopted by Pfizer to develop innovative drugs for immune-mediated and immuno-oncology diseases, shares a release by Pfizer. The platform has proved beneficial for the pharma company as it has gained multiple insights in research and development programs across over 20 diseases, adds the release.
With the emergence of new diseases, epidemics as well the urgent need for effective and safe medicines for existing diseases across the globe, researchers are now not only exploring new technologies but also combining them i.e. ChatGPT along with other AI solutions to achieve the desired results in a cost effective and much quicker time frame.
If everything goes as planned, we might just end up with numerous alternate drugs to cure every disease on this planet. We have our fingers crossed.