Breakthrough Radiology AI Provider Annalise.ai Appoints Proven Global Healthcare Leader as CEO, Officially Launches US Team Following FDA Clearances
annalise.ai, the global radiology AI company with rapidly growing presence in Asia- Pacific, Europe and the United Kingdom, today announced the appointment of accomplished healthcare technology executives Lakshmi Gudapakkam as Chief Executive Officer and clinical strategist Dr Rick Abramson as Chief Medical Officer. With the new appointments, annalise.ai expects to further accelerate its global market presence and entry into the US market following recent FDA approvals for part of its comprehensive radiology AI product.
With a mission to help one million patients every day, annalise.ai combines cutting-edge AI with clinical expertise to bring comprehensive AI products to market quickly, with state-of-the-art performance and a focus on clinical success. Formed in 2019 as a joint venture between healthcare AI platform harrison.ai and I-MED Radiology Network, Australia’s largest diagnostic imaging network, the company is focused on rapidly developing and commercialising comprehensive AI products to advance patient care.
annalise.ai products have been used to help more than one million patients since launch. Annalise Enterprise CXR, the world’s first comprehensive decision-support AI solution for chest X-rays, is already in clinical use at over 400 sites in Australia and the UK and accessible by one in four Australian radiologists. A recent peer-reviewed diagnostic accuracy study published in The Lancet Digital Health found Annalise Enterprise CXR improved radiologists’ diagnostic accuracy across 102 chest X-ray (CXR) findings*.
The company has clearance for clinical use for Annalise Enterprise CXR in Australia, the United Kingdom, Europe, South-East Asia, and New Zealand, and is expanding its products to new geographies. Earlier this year, Annalise Enterprise CXR received CADt FDA clearance for use in triage and notification of pneumothorax and tension pneumothorax on chest X-rays.
The appointment of Lakshmi Gudapakkam as CEO will help accelerate expansion plans globally and into the US along with the development of new AI radiology tools. Mr Gudapakkam brings a wealth of healthtech expertise, serving in senior global technology and business leadership roles for more than 20 years in GE Healthcare & Philips Healthcare and for the last four years with Quest Diagnostics, as their Vice President and General Manager for their East Region.
During his time with GE Healthcare, Mr Gudapakkam led large global teams across US, Canada, Europe, India, China and Australia in large, breakthrough product development for radiology imaging, cardiology imaging and healthcare informatics.
At Philips Healthcare, he oversaw breakthrough products in CT & Advanced Visualization Imaging. Later, Mr Gudapakkam moved into global business leadership roles, building up the Philips Healthcare footprint across China, India and rest of Asia. Mr Gudapakkam led large global businesses including the Global Value Segment business, Global X-ray & Mammography business and later a portfolio of global businesses including CT, Molecular Imaging, X-ray & Mammography.
During his time at Quest Diagnostics, Mr Gudapakkam oversaw expansion of the company’s diagnostic services through lab management partnerships, managing the scaling of the testing through the COVID pandemic period while leading major transformational programs including standardising IT systems and building out a mega lab in Clifton, New Jersey and consolidating lab testing in the East region.
Across his career, Mr Gudapakkam has dealt closely with both technologists and clinical experts in radiology and imaging, providing a broad network and the perfect mix of skills and business acumen to help translate complex technologies into specialist healthcare.
Strengthening its global leadership bench even further, Rick Abramson, MD, MHCDS, FACR, joins the annalise.ai team as CMO and will be responsible for guiding the company’s clinical roadmap for international expansion. A US-based physician leader and board-certified radiologist, Dr Abramson brings more than 25 years of experience in healthcare including prior roles in clinical practice, academic research, policy development, and management. Previously corporate vice-president over the radiology service line at HCA Healthcare, Inc., Dr Abramson led enterprise strategic development for radiology and artificial intelligence across HCA’s network of 185 hospitals in the US and the UK.
In his new role with annalise.ai, Dr Abramson will help advance stakeholder partnerships with healthcare providers, technology developers and regulatory bodies across the world.
Both Mr Gudapakkam and Dr Abramson will be based in the United States, supported by a strong global team of several hundred annalise.ai staff across Australia, the UK, Europe and now US with expected growth in other locations aligned with projected business growth.
Having played an integral role in the formation and success of the joint venture, annalise.ai Founding CEO Dimitry Tran will continue to serve as Director of the Board and part of the harrison.ai team. Dr Aengus Tran, Co-Founder and CEO of harrison.ai, will also continue as annalise.ai’s Chief AI Officer.
Dimitry Tran, Founding CEO and Board Director of annalise.ai, said: “We set out nearly three years ago to create a cutting-edge AI solution that empowers clinicians to make faster, more accurate decisions on radiology diagnosis. With the hard work of our global team, we’ve built an extremely strong and sustainable business with a proven model and global roadmap. To truly achieve our goals, and grow globally, we must move into the next phase of our maturity and strategy. I’m excited to welcome Mr Gudapakkam and Dr Abramson to the annalise.ai team to lead the company through this next phase of expansion and to help deliver on our mission to help one million people every day.”
Clare Battellino, Chair of annalise.ai, said: “Lakshmi is an exceptional executive and someone we are thrilled to have to help drive annalise.ai’s vision and strategy forward into our next phase of growth as a company. His approach to innovation, deep expertise in the healthtech space and established network will help to catapult annalise.ai into the future. Dimitry’s contribution to annalise.ai cannot be overstated, having tirelessly shepherded the formation and growth of annalise.ai from the beginning. We’re delighted that he will continue to have crucial input in the future of annalise.ai as a director of the Board.”
Dr Aengus Tran, Co-Founder and CEO of harrison.ai, said: “Leveraging harrison.ai’s AI capability and its leading clinical partners I-MED, annalise.ai has gone from strength to strength in taking its breakthrough radiology AI products to market. Having achieved sustainable momentum, annalise.ai is on track to help create a more equitable healthcare system for everyone. Lakshmi is well-positioned to help us achieve those goals and will ensure we have the right skills and global connections to expand our reach into new countries, new regulatory areas and new radiology products.”
Lakshmi Gudapakkam, Chief Executive Officer of annalise.ai, said: “To meet the growing demands on our global healthcare system, we need smart tools that help specialists diagnose and treat patients more effectively and accurately. The team at annalise.ai have shown an astounding ability to not only provide this capability quickly, but do so with clinical experts and patients at the forefront. I’m excited to join the team and contribute to achieving our goal of helping one million patients every day.”
*Study quote: Assisted radiologist performance — The deep-learning model statistically significantly improved the classification accuracy of radiologists for 102 (80%) of 127 clinical findings, was statistically non-inferior for 19 (15%) findings, and no findings showed a decrease in accuracy when radiologists used the deep-learning model. Unassisted radiologists had a macroaveraged mean AUC of 0·713 (0·645–0·785) across all findings, compared with 0·957 (0·954–0·959) for the model alone.