Why Clinical Evidence Matters More in MedTech Commercialization

Regulatory approval establishes that a medical device is safe and effective, but it does not always answer the questions that shape its adoption in everyday healthcare. For MedTech companies, the next challenge is building economic and clinical evidence that reflects diverse patients, real-world outcomes, hospital priorities, reimbursement pathways, and physician experience.

In an exclusive conversation with Thiruamuthan, Assistant Editor at India Pharma Outlook magazine, Anil Suri, Chief Commercial Officer, Sahajanand Medical Technologies, explores how MedTech companies can build evidence beyond regulatory requirements, connect clinical outcomes with commercial value, use real-world data to strengthen reimbursement cases, and account for physician learning curves as devices move from approval to wider adoption.

The conversation also draws on Suri’s leadership experience, offering a practical perspective on building trust, empowering teams, and leading people through complex commercial environments.

Read the complete article below for deeper insights.

From your experience in MedTech and healthcare, what have you learned about the evidence companies need beyond regulatory approval to succeed commercially?

The evidence that most regulatory agencies are seeking at a fundamental level is to establish the safety and efficacy (effectiveness) of the product, in comparison to the existing standard of care.

However, from a commercial and real-world perspective, there is a lot of diversity in patient demographics, ethnicity, disease characteristics, patient condition, etc., and therefore clinical evidence in different patient and disease types is needed to establish physician and patient confidence in those specific situations.

For example, India has a huge diabetes burden, and patients with diabetes have coronary artery disease very different from patients without diabetes. While the regulatory agency may not require a large subset of data on diabetic patients, evidence in that subset is hugely beneficial for physicians as they personalize the treatment of that individual patient who has diabetes.

How should MedTech companies think beyond regulatory clearance when building clinical evidence that can support successful market adoption?

MedTech companies should focus on building evidence in large numbers of patients, especially in the real world, to represent the diversity of the population, which is above and beyond the requirement of the regulatory agency.

With FDA approval and reimbursement decisions often requiring different evidence, how can companies design clinical studies that address both needs effectively?

Increasingly, clinical and economic evidence now go hand in hand to establish the utility of medical devices. As non-communicable disease burden is increasing and cost pressures are becoming significant, MedTech companies need to include endpoints of both clinical and economic relevance in their clinical studies from the outset. This is an increasing requirement in developed countries where healthcare spend is a significant proportion of the GDP.

While health economics vary from country to country due to different cost structures, one doesn’t need to generate such evidence in every country. There are established health economic models that can be relied upon once we have the data from one country.

How can MedTech companies demonstrate that their devices can improve patient outcomes while also delivering measurable value to hospitals?

One of the biggest values for hospitals is to deliver good clinical outcomes for patients, which is what well-studied devices can demonstrate.

In India, due to the large patient population and disease burden, hospitals often operate at full capacity and therefore the ability of hospitals to treat more patients is directly related to bed turnover rates. Therefore, any devices that can help physicians treat patients quickly or reduce hospitalization time can significantly add value to hospitals.

When an innovative device does not fit an existing billing pathway, what clinical evidence can strengthen the case for new CPT coding?

This requires close and open conversations with the regulators and the reimbursement authorities ahead of time.

For example, over the last few years, software-dependent devices have come up with a lot of diagnostic applications. While software replacing physical devices reduces the cost and time of procedures, it becomes challenging to track its usage. Business models have evolved to address those challenges, and reimbursement bodies are increasingly interested in providing reimbursement for the use of software in medical devices.

With RCTs often expensive and time-consuming, when can real-world evidence or registry data provide sufficient support for reimbursement decisions?

Real-world evidence and registry data can be a powerful supplement to small RCTs, thereby providing the benefit of large patient populations being studied. This is extremely useful to evaluate side effects that occur at low frequency, where those may not show up in small RCTs but can emerge in large registries.

Registry data can also cover diverse patient populations, thereby making evidence more representative of the country.

And lastly, health economic data and quality-of-life data can be better understood through real-world evidence or registries.

Once a device is cleared, how can companies identify gaps in their clinical evidence and determine what additional data they need?

Continuous monitoring of the safety and efficacy (effectiveness) of medical devices in the real world is extremely important. To identify gaps, close partnership and continuous dialogue with the physician community is needed. As they treat diverse patient populations, this can help identify gaps in clinical evidence beyond the data generated for regulatory approval.

How should MedTech companies account for physician learning curves when assessing clinical outcomes and building health-economic models for their devices?

This is an extremely complex question. There are many devices where the learning curve is steep and outcomes are directly proportional to the experience of the physicians. For example, there was a study in South Korea many years ago that showed centers with higher experience in treating Left Main disease had better outcomes than centers that did not have large enough experience.

MedTech companies, through their understanding of the use cases for their products and in collaboration with physicians and societies, can identify how steep the learning curve for the device is. This must be carefully factored into the commercialization strategy, and investments in training need to be made to support that learning curve.

Data must be collected and analyzed in trials looking at the experience of physicians with those devices. This is especially possible in real-world registries, which can provide meaningful understanding of the difference in clinical and health-economic outcomes across the experience curve.

Looking across your MedTech experience, what leadership principle has helped you build teams capable of navigating complex commercial decisions?

My job as a leader is to help others succeed. If one can get discretionary effort from every member of the team, success is imminent.

This is only possible through trust, which is the single most important factor that defines good leaders in my opinion. Trust can only be earned, and no titles bestow it automatically.

LAST WORD: What are five leadership lessons you would share with emerging leaders building their careers in MedTech and healthcare?

For you to lead, someone should follow.

• Trust-building is the topmost aspect of leadership.
• To build trust, be present and listen.
• To build trust, be authentic and vulnerable.
• To build trust, be empathetic.
• Actions speak louder than words.

About the spokesperson:

Anil Suri brings over two decades of experience across India, Southeast Asia, APAC, and the US, with three years at Sahajanand Medical Technologies shaping his experience in commercial growth, market expansion, and team building. His 15-year career at Abbott spanned global marketing, APAC, and Southeast Asia, giving him experience across product launches, strategic partnerships, market expansion, and commercialization.