India is now the most populous country on earth, with a rapidly evolving healthcare system. Yet, pathology on the subcontinent is keeping pace. As molecular profiling, digital pathology, and AI become increasingly central to cancer care, forward-thinking pathology leaders like Kunal Sharma are driving their implementation in the clinic.

In this interview, Sharma discusses the functional and cultural realities of implementing advanced diagnostics at scale – from affordability and validation to cross-border digital reporting and precision oncology. 

How has your role evolved alongside the rapid growth of advanced cancer diagnostics in India?

My work has evolved from purely histo-oncopathology into overseeing end-to-end oncopathology. One of the key reasons is that today we no longer treat samples simply as samples. We treat them as patients.

For example, if I diagnose a case of non-small cell lung cancer, I already know that diagnosis is only the beginning. The patient will require a comprehensive evaluation to understand the tumor biology, including biomarker testing for targets like EGFR, ALK, and ROS1. This might require target-specific assays like PCR, IHC, or FISH, or comprehensive testing via NGS.

You’re no longer issuing a standalone pathology report but building a complete molecular and diagnostic profile for that patient. That shift has made integration across histopathology, cytogenetics, molecular diagnostics, and digital systems essential rather than optional.

What are the main barriers to implementing advanced molecular diagnostics in India?

In India, a large proportion of healthcare expenditure is still paid out of pocket by patients, and insurance coverage for diagnostics has historically been limited. That made affordability a major issue for advanced molecular testing.

The real breakthrough has been our ability to reduce the cost of these assays significantly. In many Western countries, molecular tests initially cost upwards of a thousand dollars. In India, we’re now able to perform many of these tests for closer to two hundred dollars. That has made a tremendous difference in adoption and accessibility.

What factors helped bring those costs down?

A major factor has been the emergence of a strong healthcare startup ecosystem focused on genomics and oncology diagnostics. Many newer companies entered the space with highly targeted approaches, supported by private equity investment and innovation-driven funding.

At the same time, India benefits from scale. Because of the sheer volume of patients, laboratories are able to process large numbers of samples, which naturally reduces per-test costs.

Together, those factors have made advanced diagnostics much more viable in routine clinical practice.

Beyond affordability, were there other challenges to wider implementation?

Training and expertise were also important challenges in the early years. But that has changed considerably as more centers across India began offering these technologies.

Another major step forward has been the increasing number of internationally accredited laboratories, including CAP-accredited centers. That has helped standardize quality and elevate training standards.

As a result, India now has a growing pool of highly trained pathologists and molecular diagnosticians who are fully capable of performing and interpreting these advanced tests at an international standard.

How does the implementation of molecular diagnostics in India differ from Western healthcare systems?

An important consideration is that many broad molecular panels were originally developed and validated in Western populations. But the biology of cancer in India can be quite different.

For example, globally, KRAS mutations are among the most common drivers in lung cancer. But in India, a very large proportion of patients with driver-positive lung cancer, close to 50 percent in some cohorts, show EGFR mutations instead. Similarly, breast cancer in India often presents at a younger age, and triple-negative breast cancer is relatively more common compared with Western populations.

Because of that, it’s essential that these technologies are validated within the Indian population to ensure their clinical relevance and utility locally.

Are there concerns about the rapid expansion of genomic testing in India?

Yes, and this is something we need to approach carefully. As digitization and genomics become more widely discussed, there is a tendency for laboratories to enter the space very quickly and sometimes compete aggressively on pricing alone.

But molecular diagnostics cannot become a commodity without appropriate validation and quality control. Proper accreditation, rigorous assay validation, and trained expertise are absolutely critical.

Genomics generates an enormous amount of data. Interpreting that information accurately is not straightforward. In many ways, it’s like finding a needle in a haystack. You need the right platforms, the right assays, and the right people to extract clinically meaningful insights from that data.

That balance, between accessibility, affordability, and maintaining quality, is one of the defining challenges for precision oncology in India today.

How has digital pathology changed the way your organization delivers diagnostic services?

At Agilus, we support diagnostic services not only within India, but also internationally. We have operations in Dubai and work extensively with centers in Nepal, Bangladesh, the Maldives, and parts of Africa.

One of the biggest advantages of digital pathology is that tissue blocks no longer always need to travel physically for expert review. If a laboratory in another country processes the tissue locally, the slides can simply be scanned and shared digitally with our subspecialty experts here.

For example, we routinely receive digital cases from the Maldives, which our pathologists review remotely. That has significantly reduced turnaround times because the logistical delays associated with shipping material have largely been removed.

Has digital pathology also affected tissue stewardship and downstream molecular testing?

Very much so. One of the less discussed advantages is tissue preservation.

Traditionally, when blocks are physically shipped between centers, additional sections are often cut repeatedly for review or ancillary testing. Over time, that can lead to tissue depletion.

In oncology, many biopsies, particularly CT-guided biopsies, contain only limited tumor material to begin with. If the tissue becomes exhausted, you may no longer have enough material for essential molecular testing, which can ultimately force the patient to undergo another biopsy.

Digital pathology helps reduce that problem because expert review can occur without repeated recutting and redistribution of the block.

How are integrated diagnostics beginning to build on that digital infrastructure?

As we build larger digital pathology archives, we are increasingly deploying AI tools to support more objective reporting.

HER2 scoring in breast cancer is a good example. We know there can be significant inter-observer variability in interpretation. AI-assisted analysis can help improve consistency and objectivity, which ultimately supports more accurate treatment selection for patients.

At the same time, genomics is helping address some of the difficult situations created by limited tissue availability. In cases where tumor material has already been depleted, liquid biopsy approaches are becoming increasingly important.

By analyzing circulating tumor DNA, these assays can still provide insight into the molecular profile of the cancer even when tissue samples are insufficient.

So when you look at it collectively, digital pathology, AI, and genomics are increasingly converging to solve complex clinical problems in a much more integrated way.

What advice would you give pathology leaders looking to implement digital pathology and genomics successfully?

Knowledge of the importance and relevance of each testing modality is key, as is staying current with rapidly evolving testing guidelines. The standards change continuously, particularly in areas such as predictive biomarker testing.

Take PD-L1 testing as an example. Different tumor types and different antibody clones have distinct interpretation criteria. For instance, the thresholds and scoring systems used for clones such as 22C3, SP263, and SP142 are not identical. A pathologist must understand these nuances clearly because treatment decisions depend on them.

Beyond technical knowledge, what organizational changes are needed?

Pathology is changing rapidly, and organizations need to evolve with it. Across every industry, we’ve seen that those who resist technological change eventually fall behind.

Digital pathology and genomics are becoming foundational components of modern diagnostics. But adoption must be managed thoughtfully.  One thing I learned early on is that pathologists naturally have a strong attachment to traditional microscopy. You cannot expect people to abandon decades of workflow familiarity overnight.

That’s why a hybrid approach works well initially. You allow pathologists to continue using microscopes while gradually integrating digital workflows alongside them. Over time, once they begin experiencing the advantages directly, adoption becomes much more natural.

Today, AI-assisted digital pathology tools can quantify markers such as ER positivity or Ki-67 much more precisely than humans. Tumor measurements and biomarker quantification become far more objective and reproducible. Once pathologists begin seeing how these tools improve consistency and efficiency, acceptance increases significantly.

What practical challenges are especially important in developing healthcare systems?

Pre-analytics remain critically important, particularly in developing countries and smaller cities where infrastructure can vary considerably.

If tissue fixation is inadequate, if neutral buffered formalin has not been used properly, or if cold ischemia times are poorly controlled, then the downstream molecular or digital outputs will inevitably suffer.

As we often say: garbage in, garbage out.

So before implementing advanced technologies, laboratories must ensure that their foundational pre-analytical processes and validation protocols are robust. Without that, even the most sophisticated platforms will not perform reliably.

How do you make advanced diagnostics financially sustainable?

Scalability and practicality are extremely important. At Agilus, one successful strategy was deploying single-slide scanners at locations where subspecialty expertise was unavailable, including international sites.

Those centers could digitize slides locally, while expert reporting was performed centrally by our teams. That model proved highly scalable. It reduced logistical barriers, expanded access to expertise, and also made financial sense operationally.

For organizations operating within healthcare markets, sustainability matters. Technology adoption must not only improve diagnostics, but also function within a viable economic model.

When implementation is approached pragmatically, balancing quality, validation, workflow integration, and financial sustainability, the outcomes are much more likely to succeed.

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