#84- If successful, we may identify drugs to delay the spread of cancer
My chat with Arnab Roy Chowdhury, founder of Mestastop
Today I chat with Arnab Roy Chowdhury, founder of Mestastop Solutions, a biotech startup focused on predicting the spread of cancer and identifying the right drugs to fight it.
Cancer is a mortal enemy and I can not think of any family within my close circle who has not fought it. Naturally, any way to help fight it is dear to my heart.
Malpani Ventures invested in Mestastop Solutions in August 2023.
Siddharth: What I know about cancer is it's a dangerous and intelligent enemy to have. What made you want to take such an enemy on? Let's say we're in 2017, what's happening in Arnab's mind in order to dive into the world of oncology?
Arnab: A disclaimer first, I was not trained as a cancer biologist. My PhD at IICB, Calcutta and post-doctoral studies at Johns Hopkins were around Kala-azar and sleeping sickness, both infectious parasitic diseases. However, thanks to my training, I was always inclined towards therapeutic research, which probably grafted this mindset of discovery.
My first job, when I had to return prematurely from my Harvard Medical School post-doctoral studies, at Chembiotek, exposed me to the complete spectrum of drug discovery in 2003. I had no doubts about what I wanted to pursue as my profession and passion. Upon my return to India in 2009 from Johns Hopkins, I joined a GVK BIO and was soon leading drug discovery programs with big Pharma and mid-size Biotechs. During this role, I learnt the essence of the complete drug discovery paradigm, and it was only in 2010-11 did I start working on my first oncology program with GSK.
Cancer has always intrigued me, starting with a personal loss in 1999. When I got the opportunity to work in cancer, I wanted to understand as much of its biology as possible, starting from the pathways and pathophysiology. I did not want to restrict myself to the scope of the project. That learning of two-three years educated me. I became convinced that an evolutionary disease like cancer could not be tackled by identifying only targeted therapies, as the tumours soon developed resistance. My search for the weakest link in cancer brought me to metastasis, a paradox, as metastasis was responsible for most cancer deaths. By 2016 I was convinced about focussing on metastasis. At the same time, I got a job offer from Amgen In India and thought I could pursue my dreams in one of the world's largest biotech companies. Unfortunately, when I did not get that scope in Amgen, I decided to pursue my dreams independently. This was 2017. I was tired of working on other people's ideas and had enough conviction in myself to take the plunge, so I quit. It took me another year doing nothing but coming up with a scientific plan for execution, and I finally started Mestastop in September 2018. It took another year to convince some key opinion leaders and create the advisory board before I could begin the wet lab operations in November 2019.
Siddharth: What are your key takeaways from working at GVK Bio and leading discovery programs? From the outside, leading drug discovery seems very exciting. How is it from the inside? What did you have to learn, unlearn, and relearn?
Arnab: It is indeed exciting, even from the inside. The first thing I learnt was that drug discovery was a collaborative project, where one needed computational, synthetic and medicinal chemists, biochemists, cell biologists, DMPK specialists, toxicologists and in vivo animal pharmacologists, only for the early preclinical phase, where I was involved. Myself as an individual could only do very little, and it was all about acknowledging that vastness and diversity and connecting the dots. Learning potential is exponential as one constantly interacts with peers from different specializations. My role as a program leader was to see the big picture and connect the dots analytically. This training helped me somewhat understand cancer's astounding complexity, breaking it into simpler forms and then trying to connect the dots, an approach we took for demystifying metastasis.
Siddharth: What is metastasis? Why is it difficult to solve? Why is more money not going to solve it? Surprising that despite the advancement of modern medicine, this is a big problem to date. Am not very knowledgeable about the disease. What do you wish more people know about cancer?
Arnab: Metastasis means the spread of cancer, it causes 90% of deaths, and it is complex.
Metastasis, the process of tumour cells moving from one part of the body to another region and forming a second tumour in that new location, is responsible for 90% of cancer deaths. We had assumed all cells could metastasize; therefore, the larger the tumour, the higher the chances of metastasis. Naturally, all treatments focused on reducing the tumour size, surgery, chemotherapy etc. Today our understanding is different. We do realize that only some cells can metastasize, and they can do that even when the tumour is invisible under PET Scan.
The other hypothesis was this initial moving of cells from the primary tumour was rate-limiting (i.e. the slowest step out of all the steps that occur for a given chemical reaction), but our and other work clearly shows that there is more to metastasis than the movement. The ability of these cells to traverse through the blood (mainly), survive in other tissues, and then grow back to a tumour defines the success of metastasis. So no matter how many billions we spend, unless we identify what are the critical steps of metastasis other than the initial movement, we will not be successful.
Cancer can happen due to some inherent mutations over which we do not have any control, e.g. non-smokers having lung cancer. However, most lung cancer patients are smokers, which tells us there will be fewer casualties if we refrain from smoking. We can control whatever is in our hands, addictions, lifestyle, food, and stress management.
Siddharth: Let's talk about the early days of Mestastop. How do you go from an idea to achieving what you have? What did it take? What did you have to eliminate, and invalidate in order to progress?
Arnab: Our first job was to break metastasis into twelve small steps, recreate them on the bench and then test patient samples on this platform, matching them with their ultimate survival or death. We were and are still convinced that there is a typical minimum pathway for metastasis for many solid tumours, but we had to start with something so we focused on colorectal cancer. Much of the data surprised us during this journey, so we had to ask more questions. Focus was to understand the Science, to listen to the data, and not to align it with our hypothesis. This led to refining our theory, breaking it, changing it, and we finally ended up with twenty-four steps that dissected metastasis. I think the crux is acknowledging that sometimes we will be wrong and our hypothesis will be false, but if we listen to what science tells us, we can follow the right path. As a scientist, I don't want myself or my team to fall in love with their ideas. We must always be objective, alert and neutral to the data. When a hypothesis matches, we give ourselves a high five. When it does not, we spend more time understanding why.
To summarize, three and half years later, we are very confident that we have developed tools to identify compounds that will delay metastasis if intervention is done before metastasis. Unfortunately, we are yet to determine if we can reverse metastasis, which is most unlikely.
Siddharth: Does this mean if metastasis has already happened, and we're trying to treat the secondary tumour with the same medicines as the primary tumour, it is akin to treating a cold with an antacid? If the biology of every metastasized tumour is distinctly different, how many permutations and combinations do we require to create distinct drugs? Very simple question - consider two hypothetical cancers a) spread from colon to prostate, and b) spread from colon to breast - do we require different drugs to treat primary and secondary tumours?
Arnab: It's akin to treating a cold with an anti-allergy. It will not decrease your cold but decrease any unnecessary inflammation. Similarly, targeting the proliferation of the secondary tumour reduces the size of the metastatic tumour but does not delay or prevent metastasis, as the phenomenon has successfully occurred. So ideally, the intervention needs to be before the journey starts; that is, as soon as someone is diagnosed with primary cancer but has no clinical metastasis, the person should have treatment to delay the same, which clinicians term a neo-adjuvant setting.
A colon tumour that has moved to the breast or moved to the liver will get the same treatment, as most of the time, there are no specific mutations that would define their liver or lung localization. However, a breast tumour that has moved to the lung will have a different treatment than a colon tumour that has moved to the lung, as it will have other genetic traits.
Interestingly, we show that the metastasis pattern of triple-negative breast cancer and colorectal cancer has similarities, so it is possible that in the neo-adjuvant setting, the same drug can delay both breast-to-lung and colon-to-lung, or colon-to-liver metastasis.
Siddharth: So how are you solving a problem of this magnitude?
Arnab: We have broken the problem into 3 major steps, and then broken each step into multiple layers, whenever necessary. To address each of these steps, we have created one platform, thereby creating three platforms.
The first platform consists of thirty assay and characterization steps that dissect metastasis into multiple phases and differentiate between the properties of a growing versus moving cell in a laboratory setting.
The second platform is to understand which of these thirty steps are relevant in patients, so in this case, we take primary patient tumours and run them on our platform. The data generated gets integrated into a machine learning algorithm where we compare it with survival. Over some time, this tells us which steps in metastasis contribute more towards death, i.e. are critical. From this algorithm, we have identified vital stages and targets for metastasis, and we are also using the same to predict the metastasis probability of primary tumour patients.
The last platform is a high throughput animal model that increases efficiency and reduces experimentation turnover time. We have used all three platforms for multiple case studies and have shown that they work in clinical settings. For example, we tested ten approved non-oncology drugs in our first platform, selected a good and a bad one and then tested them in our second platform of patient samples and finally in the animal model platform. Data showed that the excellent drug reduced liver metastasis in the animal model, and the lousy drug was unsuccessful. We further tested this in retrospective clinical trials and the good drug stood out even in patients.
Siddharth: In simple terms, if successful what can Mestastop achieve in 5 years?
Arnab: We can
Identify approved drug combinations to delay metastasis in neo-adjuvant clinical settings
Roll out predictive diagnostics for primary patient tumours to identify patients at higher metastasis risk
Run discovery programmes on novel targets for metastasis.
Siddharth: This is unlike other businesses. Hard work (i.e R&D) is upfront. There is validation via IP and POCs before you get your first clients in. And you might not know what kind of clients actually come in later on. As a founder, how do you guide yourself and your team? What are your targets, what is your north star metric? It can't be users, revenue etc unlike other businesses surely.
Arnab: This is the most challenging question, as we have embarked on a journey based on initial belief and now validated by data, but not revenue. The north star to date had to be the Science, "listen to the data", so we can connect the dots and roll out the solution as quickly as possible. However, one cannot sustain doing basic research. The goal is to collaborate with Pharma and Biotech, with our specialized platforms, which will validate our Science and help us support ourselves. Therefore the north star will be the commercialization of our platforms in the future.
Siddharth: Despite the knowledge and track record required to start up in this field, I am assuming it is not an easy journey. It takes a village to raise a startup. Who have you partnered with in your journey?
Arnab: Â As I said, this can never be a one-person show. I was lucky to have a school friend in Praveen Agarwal, who became a Director and took over all the financial and compliance responsibilities. Then there was Dr Ajith Kamath and Dr John Ellingboe, two very experienced scientists who believed in me and became part of our Leadership team. Then came the fantastic medical oncologists, each passionate and renowned, like Dr DC Doval, Dr Anurag Mehta, Dr Govind Babu and Dr AK Vaid, who formed our medical advisory board. We collaborated with Immunobiome Inc, a South Korean company, to generate animal models. Subsequently, we collaborated with the Switzerland-based Ectica Technologies, Canada-based H10AI and our Institute of Bioinformatics and Applied Biology (IBAB).
Siddharth: You once told me that you call yourself Founder & Director, not Founder & CEO. Why?
Arnab: I am a scientist, and I would like to think that I am good at what I do, which is understanding Science and connecting the dots. I did not have a background in economics, business, or marketing, though I am learning. It is important to acknowledge each person's strengths and then play accordingly, but also equally important to recognize one's weakness and complement that with someone more efficient and better.
Siddharth: What were the naysayers saying when you started?
I was told all sorts of things, from being overambitious to being a liar and fraud. I had felt humiliated and angry, but in hindsight, it has helped me as I channelled all this into positive energy, grit and determination. The more significant picture matters, nothing else. As the great Kishore Kumar has said, "Kuch to log kahenge…"
Siddharth: What do you follow outside of Mestastop?
Arnab: I am much of a family man, but as my spouse is also a co-founder, much time at home also focuses on Mestastop. I take care of my ailing mother, who has been my source of inspiration throughout my life, and spend time with my daughters, but now one of them is in college. My sister and her two pets are an integral part of my life. I am not a social person, which is terrible, but I enjoy my solitude, Kishore Kumar, Rabindrasangeet and the occasional Khaleed Hosseini.