AiThority Interview with Avi Veidman, CEO at Nucleai

How did you start in this space? What inspired you to work in AI for Healthcare?

I knew little to nothing about the field of pathology until my father had to undergo a biopsy. The whole process was stressful, and it took 3 long weeks to finally receive the all-clear. I was at a point in my professional life where I was looking for my next challenge – I had just finished my 20-year service in the Technology Unit of the Israeli Military Intelligence Corps and I knew that I wanted to continue to practice my expertise in AI that I had honed and developed through several leadership positions in Machine Learning and Data Science. In discovering that the biopsy processes had not changed in decades, I understood that this field could be disrupted by cutting-edge visual technology imaging – and I had enough understanding and familiarity with this to dare to start Nucleai. I am inspired by making a positive impact on people’s lives and AI-powered pathology is how I am making it happen.

How difficult is integrating Machine Learning/ Deep Learning in Healthcare?

Machine Learning is propelling healthcare into a new realm of possibility with a wide range of implications. By making biopsy diagnosis more accurate, efficient and accessible, the development of novel cancer treatments is expedited by extension. While some areas in healthcare have integrated tech for many years now, the field of pathology and its processes have not changed in over 100 years! The practices for pathologists around the world have remained traditional through resistance to new tools; in my opinion, this makes the industry ripe for disruption from medical technology to improve quality and workflow. Whilst integrating new technologies is relatively simple, we are met with challenges when it comes to introducing AI into the workflows of professionals who have decades of experience working without it, no formal education on how to use it, a mistrust of the tech, and a fear that it will replace their job entirely. We have therefore built Nucleai as a solution that works with and for pathologists.

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What are the benefits of Nucleai’s products?

Nucleai is making cancer diagnostics more accurate, accessible and efficient through AI-based analysis of biopsies. Pathology is ripe for disruption as there is a major shortage of pathologists coupled with an increasing demand for biopsies. Research shows that by 2030 the number of active pathologists may drop by 30 percent compared to 2010 levels. Our team is addressing this by utilizing decades of cumulative experience in AI and machine vision to work for and with pathologists. Because of our complete product range, laboratories can integrate Nucleai’s portable, cloud-based solution to answer all their needs, instead of purchasing multiple, cumbersome point-solutions. Our tech is backed by 25 million slides and pilots have around 97% accuracy rate for diagnosis. Our ‘Digital Quality Assurance’ is built to reduce the potential for missed or erroneous diagnoses by comparing manual and automated reports and highlighted abnormalities, and our ‘Digital Resident’ increases the efficiency of pathologists by preparing reports.

How do you differentiate Nucleai from other similar providers?

Firstly, Nucleai is the only company to provide a comprehensive suite of solutions for cancer biopsies relating to colon, stomach, breast, and prostate and soon skin – encompassing 85% of biopsies. Secondly, Nucleai is a clinically oriented company, so while existing solutions in the market focus on either research or on pharmaceutical orientation, Nucleai’s solution approach is geared to actual market use, aiming to help real patients.

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Which Healthcare streams does Nucleai plan to expand?

The market for pathology tools is only growing, with potential in a variety of related disciplines including pharmaceutical companies developing new drugs, for broader Medical Research, and for direct clinical use. Our long-term vision is to develop AI-powered prognosis and prediction capabilities for Cancer treatment, providing an end-to-end platform for healthcare providers. Every year, hundreds of thousands of patients receive non-beneficial Chemotherapy treatments. In addition to discomfort and frustration on the patient’s side, this also results in huge amounts of money spent on treatment that doesn’t work. Nucleai’s enhancement technology will use AI to power prognoses and identify and suggest the most relevant treatment path for patients. 

Could you share an interesting use case when Nucleai’s solutions benefitted a hospital/client?

Nucleai has been implemented in over 10 laboratories, impacting tens of thousands of patients. Our system has performed a quality analysis of the pathologists’ work to help them locate areas that they might have missed. This provides the lab with an opportunity to work more efficiently.

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What are the biggest challenges and opportunities for the Healthcare Landscape in dealing with rising technology prices?

The challenges and opportunities for the healthcare landscape are spread far and wide. The US healthcare system, for example, is ranked as the worst among high-i***** nations, and I believe this is attributed to a number of factors – a few of which are directly impacted by rising healthcare-related costs. For example, the US spends more money on healthcare per capita than similar high-i***** countries by a long shot, partly because the prices of drugs and wages are more inflated across the board. Another factor is linked to the lack of insurance. Without a universal health care system, many people, especially underserved communities, are uninsured. Insurance is very costly and often tied to one’s employer, which creates a major gap in healthcare access across the country. I believe that to overcome existing challenges impacting healthcare-related costs. the regulatory and payer environments will need to build the right infrastructure for this to happen. We are already seeing changes in this direction from the US-FDA and some payers, and we hope this trend will continue. As this continues to evolve, we will see a healthcare industry adapted to work around this model and patients who will continue to demand newer and better solutions.

What is your take on the weaponization of AI?

Like any emerging technology, AI has immense power to be used for good or for bad. Different ethical AI groups are forming from this unchartered territory and it will take time for decision/policy-makers to catch up and regulate. For example, AI can expand our creativity as human beings and make us all more efficient when it comes to productivity output – with the end-goal being to allow humans to focus on more interesting and less tedious tasks. Yet on the other hand, if machines become smarter than us humans, or if this powerful tech is placed in the hands of people who have extreme and detriment opinions to society – our loss of control could create unforeseen and indefensible security issues.

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Where do you see AI/Machine Learning and other smart technologies heading beyond 2025?

We currently see many interesting examples of how our image analysis capabilities can help with a variety of different processes in Drug development, providing deeper insights in much shorter time frames. While looking at processes that leading companies have been doing in over a 10-year period, we clearly see that with some unique tools, these can be shortened to 1 year with a much smaller workforce. We also see many areas where patient care is not optimized and is performed by “trial and error” techniques. A strong example would be with oncology drugs that positively affect only a small percentage of people who are treated with these drugs. Today we have the technology to better predict if a certain patient will react well to these drugs or not before prescribing them, and these capabilities will only improve in the years to come.

Thank you, Avi! That was fun and hope to see you back on AiThority soon.