Imagine trying to find a needle in a haystack, but the needle constantly changes its form, and the haystack is the size of Mount Everest.
That’s a little like traditional drug discovery.
Drug discovery and development can take over a decade, and it’s estimated to cost upwards of $2.8 billion USD per drug that successfully makes it to market, once research, development, clinical trials, and regulatory expenses are factored in. Beyond that, nine out of ten therapeutic molecules fail Phase II clinical trials and regulatory approval.
With Artificial Intelligence (AI) stepping onto the stage, armed with the capability to rapidly analyze colossal amounts of data, design innovative drug candidates, optimize clinical trials, and personalize treatments, the entire process is on the brink of a revolution.
(A disclaimer: the field of AI is expanding rapidly, and so to are its applications. The information in this blog was current at the time it was posted; however, as with everything, do your own due diligence and research before taking this as current fact. TL;DR: things move fast—by the time you read this, some information may be out of date!)
Understanding AI and Its Role in Drug Discovery
In drug discovery, AI is a powerful computational tool capable of processing and analyzing vast amounts of biomedical data at lightning speed. It uses machine learning algorithms to predict target protein structures and interactions, bioactivity, toxicity, and physiochemical properties. This capability allows AI to design new drug candidates, predict how they will interact with the human body, and even optimize clinical trials by identifying the most suitable candidates.
In the traditionally time-consuming and expensive process of drug discovery, AI is changing the game. Here are some key areas where AI is making a difference:
- Predictive Analysis: AI can sift through vast amounts of biomedical data to find patterns a human might miss. For example, Insilico Medicine leverage AI to predict how different drugs will interact with the body and identify potential new therapies faster and more accurately.
- Molecular Design: AI can design new drug candidates by interpreting the complex relationships between chemical structure and biological activity. Atomwise uses its AtomNet technology to predict the bioactivity of small molecules for drug discovery. This technology can screen over a billion compounds a day, which significantly accelerates the process of identifying potential drug candidates.
- Clinical Trials Optimization: AI is being used to help streamline clinical trials, a phase often marked by high costs and low success rates. For example, Deep 6 AI uses advanced AI techniques to match eligible patients with clinical trials, greatly reducing the time to populate a study.
- Personalized Medicine: AI analyzes genetic information and patient data to tailor treatments to individual patients. Tempus, for example, uses AI to collect and analyze vast amounts of clinical and molecular data, aiming to make precision medicine a reality.
The Impact of AI on Pharma
Traditionally, drug discovery has been a painstakingly slow process, often taking years, even decades, to identify promising compounds. AI advancements and uses (as outlined in the previous section) are reducing the time to identify potential drug candidates significantly. This acceleration doesn’t just speed up the process, it also translates into faster time-to-market for life-saving drugs, a critical factor when dealing with rapidly spreading diseases or global health crises like the COVID-19 pandemic.
The advancements in accuracy and precision dovetail with significant economic implications. The traditional costs of bringing a new drug to market can run into billions of dollars, with substantial resources spent on unsuccessful trials. The introduction of AI into the mix has resulted in improved efficiency and substantial cost savings, making the entire process more sustainable.
What Are the Problems AI Drug Discovery is Facing?
One of the significant challenges of AI drug discovery is the acquisition of high-quality, extensive data on molecular structures, biological activities, and patient responses, particularly during clinical trials. The associated processing power required to analyze and interpret this vast amount of data is also a cause for concern. Vast amounts of very specific data and processing power are the bedrock upon which AI models are built and refined.
After gathering the input data and necessary computing power, researchers need to be able to interpret the system’s output and how the AI came to a decision. In other words, overcoming the “black box” problem of AI (where decisions made by algorithms are difficult to interpret). This poses a challenge in understanding the effectiveness and safety of potential drug candidates suggested by AI. If we can’t understand why a system came to a certain decision or verify that decision, then the result isn’t useful.
This is where AI safety and regulations come into effect. As AI’s role in drug discovery (and other facets of pharma research) expands, it must navigate stringent regulatory scrutiny to balance innovation with safety. In fact, the FDA and EMA are developing new risk-based regulatory frameworks to ensure that the use of AI in drug discovery is verifiable and safe.
The Future of AI-Driven Drug Discovery
AI and machine learning are increasingly becoming integrated into many different facets of our lives, from work to entertainment and healthcare. As these models engage the drug discovery process, it’s important to establish a symbiotic relationship between AI systems and human experts. While AI will handle the brunt of data processing and pattern recognition, humans will need to provide the context, intuition, and verification to bring safe and effective drugs to the market.
High Touch Group is a specialty marketing agency that helps science and engineering clients market existing products and services, showcase their value, develop, and launch new products, engage with investors, generate leads, and drive revenue.
For more information about our services, contact us today.
