Accuracy, Prevention, and the Prospects for Innovation in Healthcare

Driven by the exponential growth of genomics, Artificial Intelligence (AI) and molecular computing, the healthcare industry is rapidly shifting towards personalised, technology-enabled solutions and also radically reshaping the life sciences landscape. Hiranjith H, a healthcare and life sciences executive who has over 15 years of experience in the U.S., is at the helm of this transformation.

Currently serving as the Chief Business Officer at Algorithmic Biologics, a deep-tech healthcare company specialising in molecular computing, Hiranjith also holds the position of President & Board Member at EPPIC Global, a California-based life sciences non-profit innovation platform that connects global entrepreneurs, investors, and industry leaders.

In conversation with Shahid Akhter, Consulting Editor at FE Healthcare, Hiranjith discusses the changing nexus between biology and technology, the potential of preventive medicine, the difficulties of large-scale innovation, and how India is becoming a key player in determining global healthcare solutions.

What trends do you see in the healthcare technology space that you are excited about?

The practice of medicine and biology research has become more targeted and personalised over the last decade or so, driven primarily by our understanding of genomics and proteomics. We are now witnessing our ability to execute precision or personalised medicine at scale,  driven by our advancements in technology to generate data and tools to generate insights. We are also looking at multi-omics data (DNA, RNA, protein and methylome) being generated from samples that give us a better picture of the biological processes involved. And with the adoption of artificial intelligence tools, our ability to aggregate data and generate insights from multi-modal data for target discovery, disease diagnosis, treatment, monitoring, and disease management decisions have improved significantly in recent times.

With a better understanding of markers for disease and wellness, we also have an opportunity to leap into preventive medicine by building cost-efficient and effective screening assays that can enable population-level screening for public health initiatives. We see a lot of disruption in life sciences innovation recently. First and foremost, organisations and institutions are looking to achieve objectives in a budget-constrained environment. 

Academic research is exploring innovative ways to fund their research, like private funding to augment the limitation with government grants.  Small biotechs are evaluating their runway and devising strategies to extend the same -– reprioritisation of research programmes, diverting resources to clinical programs and M&A frenzy are top of mind for the corporate development teams.

 Public health programmes, even though equipped with innovative tools for screening and management, have to build programmes that can scale. With our access to GPUs and AI technologies, data is the new oil. 

Organisations have to balance their data strategy to include both public and proprietary data sources while building their product and solution roadmap. Proprietary data is also seen to offer a competitive advantage to organisations as the industry adopts AI. 

Your observation and current involvement 

Over the past 15 years of my involvement with the US life sciences industry, I have observed that with the above advances, we are trying to achieve faster target discovery, faster rollout of diagnostics and population screening assays, and faster clinical reporting (in hours instead of days). In alignment with providing better patient outcomes eventually. 

My current efforts at Algorithmic Biologics, founded by Dr. Manoj Gopalkrishnan, PhD, strive to address some of the above needs of the industry. Our molecular computing platform enables in vitro compression for biological samples or sequences, achieving scale efficiencies that were previously limited. The applications are immense– accelerated assay designs and validation, cost optimisation for population-scale data generation or screening, and building very comprehensive diagnostic assays that were previously limited by technology constraints. We are one among many healthcare technology and AI companies that are pushing the envelope to make precision and preventive medicine more affordable and effective globally. 

What opportunities and challenges do you see for healthcare technology companies to contribute towards global life sciences innovation? 

The above trends lend a lot of opportunities for healthcare technology companies. With strong capabilities in biology, technology, cloud, AI, and delivery, healthcare technology companies can add a lot of value to life sciences innovation. Focusing on disease-specific solutions for diagnostics, biomarker discovery, companion diagnostics, clinical trial digitisation, clinical decision workflows, and many more. Healthcare technology companies can also help build platforms that integrate geographically diverse datasets for many of the above applications in a seamless and secure manner. This helps to bring healthcare equity to practice. With efficiency improvements driven by automation and AI, the cost of healthcare delivery can be optimised as well once the solutions are implemented and adopted by healthcare stakeholders. 

In practice, the technology can be developed globally. With scientific expertise and technology expertise available globally, building these tools and platforms can be a global effort, much like how India built its software development, implementation, and maintenance muscle during the dotcom boom. 

How do you see India playing a role in this?

We are seeing the growth of Global Capability Centres in India by major pharmaceutical companies, providing services and solutions across the value chain, which is a testament to the acceptance of India’s talent in the global stage. We, at AlgoBio, built our proprietary Tapestry and Sequence Transduction technologies for in-vitro compression in India but recently launched them in the US through partnerships and collaborations for targeted use cases.

What challenges do you encounter in building healthcare technologies?

While building healthcare technology solutions, one of the key challenges will be to implement data security guardrails that are accepted globally. Clear IP protection and sharing engagement models will be key to longstanding partnerships as the stakes are higher. And as in any global engagement, execution methodology and processes adhering to global best practices will be necessary to succeed in these engagements.

Overall, I see a large integration of technology into healthcare solutions. And one that will be fueled by players that are building it from different parts of the world with global impact!