“qSpot-TB will play a vital role in TB detection and screening amidst evolving public health challenges”: Bunty Kundnani, Qure.ai

In this email interview to DHN, Qure.ai’s chief regulatory affairs officer, Bunty Kundnani explains what the FDA Breakthrough device designation means for their solution.

The FDA's Center for Devices and Radiological Health (CDRH) last month designated qSpot-TB developed by Qure.ai, a breakthrough device designation. A pioneer in medical imaging AI, Qure.ai’s Artificial Intelligence powered solution will aid in TB detection and screening.

Over the past 18 months, Qure.ai has received 61 CE mark approvals under the European Union Medical Device Regulation (EU MDR), four FDA clearances.

The significant development comes at a time when tuberculosis cases have shown an increase post Covid-19 pandemic.

In this email interview to DHN, Qure.ai’s chief regulatory affairs officer, Bunty Kundnani explains what the FDA designation means and what are the future plans of the company.

Edited excerpt:

Q. Congratulations on receiving the breakthrough device designation from the FDA for qSpot-TB. How does this designation impact the regulatory pathway for your AI-powered TB solution?

Bunty Kundnani: Receiving the breakthrough device designation from the FDA for qSpot-TB is a significant milestone for Qure.ai. This designation expedites the regulatory pathway for our AI-powered TB solution, enabling us to engage in streamlined discussions with the FDA focused on the safety and effectiveness of qSpot-TB. It facilitates expedited review and clearance processes, allowing us to bring this innovative solution to market more swiftly and efficiently to address critical unmet needs in tuberculosis diagnosis and management.

Q. How does qSpot-TB function as a second-read computer-aided detection and diagnosis device for TB, particularly in analysing Chest X-rays? What sets it apart from traditional diagnostic methods?

Bunty Kundnani: qSpot-TB serves as a second-read computer-aided detection and diagnosis device for TB by leveraging artificial intelligence to analyse chest X-rays. Unlike traditional diagnostic methods, qSpot-TB offers advanced capabilities in detecting radiological signs of TB with high accuracy and efficiency. Its AI algorithms enable rapid analysis of chest X-ray images, providing healthcare professionals with timely insights to aid in diagnosis and treatment decision-making. This technology augments clinical workflows, improving diagnostic accuracy and patient outcomes while optimising resource utilisation in healthcare settings.

Q. With the recent uptick in TB incidences in developed nations, how does qSpot-TB support clinical workforces in these regions, especially in prioritising patient cases and expediting decision-making processes?

Bunty Kundnani: In regions experiencing an increase in TB incidences, such as developed nations, qSpot-TB plays a crucial role in supporting clinical workforces. By providing timely and accurate TB detection capabilities, qSpot-TB helps prioritise patient cases based on severity and urgency, facilitating expedited decision-making processes. Its AI-powered functionalities enable healthcare providers to efficiently allocate resources and interventions, ensuring that patients receive timely diagnosis and treatment, thereby mitigating the spread of TB and improving overall clinical outcomes.

Q. Qure.ai emphasises its commitment to adhering to rigorous legislative and regulatory processes in over 85 countries to ensure safety and efficacy standards for its solutions. Can you discuss the challenges and opportunities encountered during this regulatory journey?

Bunty Kundnani: Qure.ai is committed to upholding the highest standards of safety and efficacy for its solutions, which entails navigating complex regulatory landscapes in over 85 countries. While this presents challenges such as varying regulatory requirements and timelines, it also offers opportunities for collaboration and innovation.

Our team actively engages with regulatory authorities worldwide, fostering transparent communication and compliance with evolving regulatory frameworks. By leveraging strategic partnerships and expertise, we address regulatory challenges effectively, ensuring that our solutions meet global standards and contribute to advancing healthcare outcomes on a global scale.

Q. TB cases in the United States experienced a notable increase in 2021/22, following a prolonged decline. How does Qure.ai foresee qSpot-TB contributing to TB detection and screening efforts amidst evolving public health challenges like the COVID-19 pandemic?

Bunty Kundnani: As TB cases continue to rise, qSpot-TB is poised to play a vital role in TB detection and screening efforts amidst evolving public health challenges like the COVID-19 pandemic. Its AI-powered capabilities enable rapid and accurate TB diagnosis from chest X-ray images, supporting early detection and intervention. This is particularly crucial during the pandemic when healthcare systems are under strain, and timely diagnosis is essential for controlling disease transmission. qSpot-TB's scalability and adaptability make it well-suited for integration into existing healthcare infrastructure, enhancing TB screening efforts and contributing to effective disease management strategies in the face of evolving public health challenges.

Q. What are some of the key considerations regarding the safety, efficacy, and scalability of qSpot-TB as it undergoes further regulatory review and implementation in various healthcare settings worldwide?

Bunty Kundnani: Safety, efficacy, and scalability are paramount considerations as qSpot-TB undergoes further regulatory review and implementation in various healthcare settings worldwide. Ensuring patient safety and the accuracy of diagnostic results remains a top priority throughout the regulatory process. Additionally, qSpot-TB's scalability is essential to meet the diverse needs of healthcare systems globally, from resource-limited settings to advanced healthcare facilities. Our ongoing focus on rigorous testing, validation, and continuous improvement ensures that qSpot-TB delivers consistent and reliable performance across different healthcare environments, ultimately enhancing its impact on TB diagnosis and management on a global scale.

Q. Qure.ai has achieved several FDA clearances and CE mark approvals in the past eighteen months. Looking ahead, what are the future milestones and developments that you aim to achieve, both in terms of regulatory advancements and clinical impact?

Bunty Kundnani:- Looking ahead, Qure.ai remains committed to advancing regulatory advancements and making a meaningful clinical impact with our innovative solutions. Building on our recent FDA clearances and CE mark approvals, our focus is on expanding market access for qSpot-TB and other AI-powered solutions globally. We aim to further strengthen our regulatory partnerships and streamline clearance processes to accelerate the availability of our solutions to healthcare providers and patients worldwide. Additionally, we continue to invest in research and development to enhance the capabilities of our AI algorithms and address evolving healthcare challenges, ultimately improving patient outcomes and advancing public health initiatives on a global scale.