Meet ADITYO PRAKASH(CEO of Verseon)

Tell us about Verseon. How does it fit into the modern pharmaceutical industry?

Verseon is a high-tech company whose end products are therapeutic small-molecule drugs that could change the standard of care for many of today’s challenging diseases. Small-molecule drugs are the mainstay of the modern pharmacopeia. They are low-molecular weight organic molecules that can enter cells to interrupt disease processes and can typically be administered orally.

While pharmaceutical medicines—and small-molecule drugs in particular—have made great strides over the last century in treating diseases, many challenges remain. There are still many medical conditions that current medicines either cannot treat or can only treat poorly. Novel therapeutic interventions are critical to the future health and well-being of humanity.

At Verseon, our goal is to transform drug discovery and create a steady stream of precision treatments for major diseases. To accomplish this, we’ve made a number of scientific breakthroughs in physics- and AI-driven molecule engineering that allow us to systematically design new, promising drugs that possess unique pharmacological properties and are unlikely to be found by any other current method. We have already successfully applied our platform to various diseases to generate a large number of highly promising drug candidates that are starting to progress through clinical trials.

What are some of the challenges in the drug discovery process that Verseon is trying to solve?

All other current methods of drug discovery rely on trial-and-error testing of a few million distinct compounds that have already been synthesized. And most of today’s “AI-first” approaches focus on ingesting available experimental data and attempt to make predictions that might reduce the amount of trial-and-error testing within the field of known drug-like compounds. But these methods only skirt around the fundamental problem of drug discovery: the inability to find completely new drug molecules that have never before been synthesized anywhere. So, the industry typically finds “me-too” compounds that are very similar to previously studied molecules or repurposes existing drugs. And the ROI on drug research continues its long-term downward trend.

While the industry is currently limited to exploring a few million compounds and their associated data sets, a billion trillion trillion—or 10³³—other possibilities remain completely unexplored. It’s in this vast unknown ocean of possibilities that truly novel small molecules with unique pharmacological properties can be found.

That’s where Verseon comes in.

We’ve spent a decade and a half developing fundamental advancements in computational chemistry, molecular-physics modeling, and applications of AI to make systematic design of completely new drug molecules a reality. For any disease-causing protein of interest, we can explore hundreds of millions of never-before synthesized drug-like molecular structures and computationally identify the best binders to advance into computer-directed synthesis and biological testing. Our proprietary physics modeling and AI-based methods allow us to sidestep the synthesis bottleneck and limited data sets that thwart the rest of the industry and find novel drug molecules with uniquely desirable properties that have the potential to change the standard of care for every disease we address.

How is AI helping in the drug discovery process for Verseon?

AI in various forms now permeates almost every step of our drug discovery process. But it is a thoughtful application of context-appropriate AI methodologies coupled with other scientific advances.

In some instances, AI helps improve the dynamic exploration of novel chemical matter by better leveraging knowledge associated with the target protein. Within our molecular-physics modeling engine, AI helps improve the accuracy and speed of our free-energy estimations. Other AI modules utilize comprehensive experimental test data from our novel chemicals to help us more efficiently explore adjacent regions of the chemical space and propose structural modifications that improve various pharmacological properties. Further downstream, there are early signs of positive benefit in utilizing AI-based analysis of clinical trials.

What are some of the diseases Verseon is initially targeting with its drug discovery platform? Can you name some of the novel drugs in your pipeline?

Most of our current drug programs fall under two broad categories: cardiometabolic disorders and cancers.

Within the cardiometabolic disorders category, I’ll highlight two programs. Our Precision Oral Anticoagulants—or PROACs—and our oral prophylactics for diabetic vision loss.

Well over 100 million patients in the developed world need some form of life-long anticoagulant therapy to prevent heart attacks and strokes. Of those, a staggering 51 million patients could benefit from combination therapy with both an anticoagulant and an antiplatelet drug. Unfortunately, current anticoagulant drugs, many of them blockbusters from major pharma companies, all carry unacceptably high bleeding risk and are entirely unsuitable for long-term combined administration with an antiplatelet drug.

Our PROACs work through a unique mode of action by which they prevent clot formation and yet do not impair platelet function or significantly increase bleeding risk. This positions them to be the only drug candidates suitable for safe long-term combination therapy with antiplatelet drugs to prevent life-threatening strokes and heart attacks in this very large patient population.

Our most advanced PROAC candidate, code named VE-1902, has been delivering promising results and is nearing the end of Phase 1 trials. Our second candidate, VE-2851, has successfully completed preclinical tests and is ready to follow VE-1902 into clinical studies.

Diabetes is a disease that leads to many unpleasant life-altering problems. One of the most common is diabetic retinopathy—also known as DR—which affects over 35 million patients in the developed world. DR can lead to vision loss caused by blood vessel leakage in the retina. The current standard of care is to simply wait until vision loss is severe enough to justify regular injections into the eye with repurposed cancer drugs to treat the symptoms.

We have developed a novel class of oral drug candidates that could act as prophylactics, giving diabetics a chance to prevent this form of vision loss altogether. Our candidates are the only ones to successfully demonstrate reduction of blood vessel leakage in relevant in vivo tests. Our most advanced candidate, VE-4840, is ready to enter clinical trials.

In the arena of cancers, I’ll mention two examples: our novel chemotherapy agents for multidrug resistant cancers and our first immuno-oncology program that targets an overexpressed protein present in half of all solid-tumor cancers

While chemotherapy remains the first line of treatment for most cancers, too often resistance develops to multiple chemo drugs. Sadly, multidrug resistance causes 90% of cancer-related deaths that occur among chemo patients. In preclinical tests, Verseon’s novel chemo drug candidates have shown that they don’t lose effectiveness even when these cancers develop resistance to other drugs.

Our first immuno-oncology program focuses on CD73, a protein cancer cells frequently overexpress to mask their presence from the immune system. Verseon is developing a novel series of non-nucleotide CD73 inhibitors, fundamentally distinct from other compounds currently in development, that hold promise to reactivate immune response to CD73-positive cancers.

Again and again, what we find is that our ability to explore uncharted chemical space allows us to find drug candidates with uniquely desirable properties for the treatment of every disease we address.

Can you list some of the biggest challenges that Verseon has had to overcome?

Building a platform capable of systematic drug discovery and development is no small undertaking and required more than a decade of intensive work to achieve. As Sang Kim, our newly appointed CTO and a member of the National Academy of Engineering, so eloquently points out, “Verseon’s platform is comprised of significant new advances within multiple distinct branches of science. Each of these advances would be enthusiastically welcomed by the leading practitioners in their respective domains—but the collection of these advances is virtually unattainable by any other organization.”

Such a long development arc not only requires the right combination of talent, inspiration and luck to come together to solve hard scientific problems, but also the wherewithal and drive to weather various global macroeconomic events that can affect the entire industry.

Speaking of scientific and technological development, there were parts of the process we thought were sufficiently simple that we wouldn’t have to build them in house and could just in-license. But when we needed to put those technologies in place, we discovered that no one else had ever built viable versions of those tools. In order to create a system that actually works, we had to build those pieces ourselves.

Navigating the major political and economic shifts during our platform development process was no mean feat either. For example, the 2008 crash impacted our development speed as economic activity and investment in our sector dramatically slowed. More recently, operational constraints posed by the current pandemic have included logistical challenges to conducting clinical trials, and companies like ourselves have had to adjust.

Despite various challenges over the past two decades, we have had a rewarding journey as we find ourselves in a position to positively impact global health.

What do you foresee as some of the biggest trends and challenges for AI in drug discovery?

In my view, the current state of AI in drug discovery strongly resembles the dot com boom of the late 1990s. Many companies simply use AI as a buzzword to make their products and services more marketable and bolster their share price. Such companies will see their prominence in the drug discovery space wane over time, and perhaps disappear when the inevitable shakeout comes. Other companies will create genuinely useful tools that will endure, but from what I’ve been able to observe, those companies will be comparatively few and far between.

My position is that the companies making the best use of AI will be the ones that couple AI techniques with significant advances in many other scientific arenas to make the discovery of completely new drugs more reliable, robust, and streamlined. Those companies will be the new leaders in the field of pharmaceutical medicine. Verseon plans to be foremost among them.