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“Leading Somebody Is Like Serving Somebody" Chairman, Co-founder Partex NV
"We are looking at collaborating across the silos using the three-element approach." CEO, and co-founder Partex,
Photo Credit : Reuters
In an interaction with Urvi Shrivastav, editorial lead, BW ESG, BW Businessworld; Dr. Gunjan Bharadwaj CEO, and co-founder Partex, and Francisco Fernandez, Chairman, co-founder, Partex speak about the company, Artificial Intelligence (AI), healthcare sector, and leadership for upcoming entrepreneurs.
Why did you start Partex? What does it do?
Dr Bharadwaj: A friend of mine was diagnosed with cancer in 2010. Disease and death are very abstract concepts until you see it up close. That is where we saw the challenges in the healthcare sector. We wanted to come out with a technique that does not look at drug discovery and development in a traditional way. Partex looks at three elements, one is democratisation of patient data, industry and healthcare, providing the lion's share of the value of patient's data back to the patient. The second is innovating using artificial intelligence. So looking at traditional decision-making in pharma using real-world validation, but augmenting that with AI using all the medical knowledge of the world which is doubling itself every 73 days. Third is using collaboration to unlock talent in the big pharma pipeline because big pharma look at their hypothesis in a traditional way. We are looking at collaborating across the silos using the three element approach.
How will you use AI to scale up the business?
Dr. Bharadwaj: AI can be used in three ways, one is from an efficiency perspective, for example, 55 per cent of the time of every scientist goes is going through extensive research and generates hypotheses. This time can be replaced by an AI engine that scans all the scientific literature out there and comes out with the hypothesis which will have the greatest probability of success at a push of a button. Second, you can look at innovating and accelerating drug discovery, looking at some of the hypotheses that could be very counterfactual. We all have an intrinsic bias based on what we study, and where we come from. This happens in the real world as well. If you have a clinical development head that has worked in Oncology, he would prefer an indication of disease in oncology based on the drugs he/she has had. AI is unbiased and you will need all the data in the world to come out with counterfactual hypotheses. That way you can look at ideas that are not very obvious, that propel, innovation. The third is the aspect of data, where we are leveraging AI. If you were to create a marketplace where patients can leverage their own data, for that matter any user can license of trade his or her own data, you would need a mechanism to summarise the data. Your medical data would be data could be used over a long period of time. The challenge is to summarise this data, in a way that is succinct. That summary a doctor can provide whenever they look at your report, AI can also do that. It is called abstractive summarisation, and with that you can generate summaries with long texts, and books, for people who want to read only the summary. We leverage AI to make the summary of patients. This will help monetise their own data.
Fernandez: We do not use AI to expand our business, we are AI. It is at the core of our business. While other companies are using tools like biology and medicine, we are using AI, blockchain and the like. While we want to work on the same problems, the focus is not on making a new molecule but looking at the same problem from a different lense. AI is not used to scale our business, it is our business. That is why we call ourselves digital pharma.
You have a venture called ‘Amrit'. What is that about?
Fernandez: AI becomes more smarter with training, and training for AI means vast amounts of data. We collect data from over 10 billion URL every day. Everything that is publicly available we extract and process. The other part of the data is private data, and probably the most confidential is health and wealth data. I say this because I have set up some of the largest fintechs in the world. Now we take care of wealth data. Other big companies are using our data without even our knowing it. They monetise the data without user participation. They also don't invite the user to participate in data usage or monetisation. We go the other route, we tell people we want their data, we are going to work with it for a greater good, we are going to find new drugs, cure diseases, and then sell that data to somebody who can work with it. By doing this the user is going to monetise too and will be the first profiteers. Amrit has created patient apps that help patients answering these pressing questions, like where they can participate in modern clinical studies with modern therapies, and who is the absolute expert in their condition. The confidence in our application has brought about the download of two million apps. We have already indexed and processed data of 350,000 within less than a year.
How can we use AI to take the healthcare industry forward as a whole?
Fernandez: Artificial Intelligence works just like scientists. Except a scientist can look at only as much data as a human being can absorb. But AI can read through millions of papers in a few minutes, no human being can do that in an entire lifetime. So how can we take the entire human data of the planet, read it, understand it, and contextualise it. There is no human power that can do that. Only AI can do that, and try to find new combinations, co-relations, ideas, etc. AI should not be seen to replace humans yet but to leverage humans to come up with the information they did not have access to before.
Dr. Bharadwaj: A similar approach is being applied to other industries like EdTech. It would be interesting to know about our business ‘Notera' which has a substantial presence in the Indian EdTech space.
Fernandez: It is a pure AI product, like Partex. It is again a large problem to solve, namely, to feed the planet with sustainably created food. When we arrived here, we wanted to start helping the dairy industry. We found the majority of the milk was laden with Alpha Toxins and antibiotics, and other pollutants. We wanted to solve that issue. When we came here, we saw cows that gave two liters of milk a day, and the best ones gave 40 liters a day. There is more to the story than an inferior-style cow. There is a lot of knowledge missing here, even though we have 100 million farmer families. With scientific knowledge, by using technology they cannot afford yet, by putting sensors in the soil, drones over fields that analyse what is the problem with the plants, and by predicting if the situation is much better via satellite images and technology. By face recognition of the cow, by analysing via face recognition of the cows, to analyse if the cows are sick. There are so many things you can do by bringing technology to the farmers. The other thing is, food is a scale problem. Soon we will have to feed 10 Billion people globally, and if we go by this rate it will kill us. If we look at some poultry factories, we will realise it is the number one producer of resistant bacteria and viruses, also because they don't understand the dosage of antibiotics within these gigantic factories.
However, if you want to scale the food business, scale the farmer. That is how you have these gigantic mono farms in Latin America. However, it comes with its problems. Scaling pollutes the air, the ground water, and soil. Post internet you have the opportunity if interconnecting 100 million farmers. One gigantic virtual farm, and you also have the scalability synergies. As a network of farmers they will have more power for scalability than a single farmer. So we try to educate and empower the farmer to produce more at a higher quality with lower risk. We now have 350,000 farmers on the platform and one platform is to help them do better, the other is to help them trade their produce at scale, also by using data to give better price predictions. These farmers are in India and the Philippines as well. We sell this product domestically and also export it to China.
What are the loopholes in the pharmaceutical sector, and how will you address them?
Dr. Bharadwaj: I would not say loopholes, but there are three challenges that we see. The first one is, the patient being at the center. A lot of pharma claim that is so but it is far from reality. When you talk about patient data, people start talking about philanthropy, they should share their data as it is good for society. But when it comes to big pharma selling their drugs, people forget philanthropy and they want cash. We believe a patient has to be truly at the center and you can bring patients truly at the center by increasing awareness, and by helping them understand and appropriate a lion's share of their own data. Second, we have to accelerate the pace of innovation. Covid triggered this acceleration, people started working together, people started leveraging virtual clinical trials, more coordination, etc. We believe AI combined with real-world validation is the answer. Innovation-driven leveraging AI is the second bit. The traditional pharma process looks at biology, and chemistry in a very traditional way. The third is collaboration, you can't think in silos, you can’t optimise the drugs you have in your pipeline, and you eventually have to think of a patient. Many diseases require a combination approach. I would say these three are the main challenges.
What would your advice be for entrepreneurs in India?
Fernandez: Being a successful entrepreneur is strongly linked to innovation. The idea is to create new solutions for old problems and innovation is linked to culture. This includes challenging the status quo, thinking out of the box, and that requires two things. The first is, you don't think in a hierarchical way because CEOs are not innovators. They are managers who organise work. When you think of innovation you never know where the next best idea is coming from. It can come from the cleaning lady, the architect, or a finance professional. So you have to listen to and respect everybody. This goes against the hierarchical belief in the Eastern world. We have two advice one is for the people below, the led, who should dare to challenge the status quo and challenge their boss. My advice to the boss is, you need new styles of leadership styles today. I call that ‘servant leadership'. If I am your boss, you don't work for me, I work for you. It is my role to make you excel. If I can do that to my whole team, I will prosper from your excellence as well. But it is my job to serve you to be even more excellent. Leading somebody is like serving somebody. You have to turn the narrative in your head around. The other thing is innovation is closely related to the culture of risk-taking. In all of Europe, if you fail once, you will never again get credits, money, or respect. In the US you have to fail twice to he respected. Failure culture is important, but not just that there is also a need for a culture of risk-taking. Risk capital is also something you support people with dreams, new solutions, and novelty. You have to support them because even if 80 per cent will fail, the other 20 per cent will succeed. This can change the world