In this interview, we speak to Jukka Tapaninen, CEO of Aiforia Technologies, exploring how their AI-based technology helps to optimize the workflow of clinical pathologists. Learn more about the progression of digitalization in the healthcare sector, and the benefits AI can bring to clinical research.
Please could you introduce yourself and tell us about your role within Aiforia?
I am Jukka Tapaninen, Chief Executive Officer at Aiforia Technologies. I joined Aiforia as the CEO in 2020 after over 25 years of experience in various executive positions at international IT and software businesses such as SAP and HP. I also previously served as a board member of Aiforia before joining the executive team as CEO.
Aiforia’s solutions aim to alleviate the pressure pathologists and, more broadly, healthcare systems face. What do you believe to be some of the biggest challenges currently faced by pathologists and healthcare systems?
Pathologists are crucial to healthcare systems, evaluating and diagnosing patient samples to help guide medical treatment and prognostics. Populations are aging at a rapid pace and diseases like cancer are on the rise. This creates a huge burden on pathologists and hospitals around the world.
According to the World Health Organization, by 2050 the proportion of the population aged 65 years and older is expected to increase from about 9% to 16%, and cancer prevalence is expected to rise by nearly 50% by 2040.
There is currently a serious imbalance. Rising numbers of patient samples created by the conditions I just mentioned, which are exacerbated by the fact that fewer doctors are specializing in pathology so there are workforce shortages, are mismatched by the fact that pathologists are still relying on the same technology that has been around for the past 150 years; manual slide analysis with microscopes. This methodology for evaluating patient samples is not only slow but also prone to variability.
So pathologists worldwide are overworked, patients are waiting for increasingly longer times to receive results, and in some cases can be administered ineffective treatments due to misdiagnosis or the inability to administer personalized treatment. Pathology is ready for paradigm-shifting technology to alleviate the burden experienced by both pathologists and patients.
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Your AI-assisted image analysis platform aims to address the pressures faced by pathologists. Could you tell us more about how this technology works and how it improves not only the daily working lives of pathologists but the accuracy of diagnoses such as cancer also?
While the digitization of pathology is enhancing lab workflows and enabling more efficient collaboration, digital pathology is not the only answer to addressing the concerns of rising caseloads and significantly improving patient outcomes.
After all, effective treatment begins with a precise diagnosis. At Aiforia we are providing and developing solutions that equip pathologists with the AI-powered tools they need to not only accelerate sample review and to substantially increase productivity, but to also improve diagnostic accuracy to ultimately save more lives.
The Aiforia Clinical Suites will provide diagnostic support to pathologists in numerous ways. By automating repetitive tasks, pathologists can increase the speed and accuracy of diagnosis, giving them confidence in their decision-making and freeing more time to focus on rare and complex cases.
The Clinical Suite is beneficial in areas with a lack of pathologists and specialists, providing those few existing healthcare professionals a helping hand. The benefits experienced by both healthcare systems and patients are manifold, such as decreased waiting times for diagnosis, reduced healthcare costs and more personalized treatments.
What is ‘deep learning’ and how does it factor into Aiforia’s platform?
Deep learning is a form of artificial intelligence; it is the next generation of machine learning. As a more autonomous and advanced form of AI, it is incredibly powerful at image recognition and analysis, already surpassing human capability in these tasks. It is considered a major technological advancement in healthcare.
At Aiforia, we have built state-of-the-art, user-friendly software for healthcare professionals across a wide range of disciplines to have access to deep learning AI without any restrictions.
End-users can create their own deep learning AI models, or algorithms, with Aiforia’s software simply by annotating their images to train our neural networks to learn how to identify, quantify or measure any feature in any image, ultimately automating that task.
There is no need to code or use dedicated hardware for researchers, scientists and pathologists to deploy AI through our platform. So far, our users have developed over 400 AI models for use in fields like oncology, neuroscience and many others.
AI technologies are becoming a staple across a myriad of industrial sectors. Why are they especially suited for clinical diagnostics and analysis?
AI in clinical diagnostics, specifically when used by pathologists, offers great benefits in scaling productivity, helping to increase diagnostic accuracy, reducing costs, enhancing staff satisfaction and improving patient outcomes.
Artificial intelligence is substantially faster at image analysis and enables the automation of manual, time-consuming tasks. Speeding up case reviews increases the output of pathology labs, allowing more new patients to be taken in. Additionally, with the time saved, pathologists can focus longer on complex and rare cases.
These AI systems have also been proven to improve the accuracy of analysis in clinical pathology; AI models can reduce bias and standardize sample review, democratizing care given to patients.
At Aiforia, you offer a range of solutions that differ depending on industry and application. What is the difference between Aiforia’s solutions, and how important was creating tailor-made solutions for Aiforia and your clients?
Aiforia Technologies offers solutions for the preclinical and clinical markets. The preclinical industries include contract research organizations, pharmaceutical, biotechnology companies, and academic institutes seeking solutions for both medical research and education.
Our established base there has enabled us to enter the clinical diagnostics market. We recently came out with two CE-IVD marked AI models for supporting pathologists in diagnosing breast and lung cancer and have other clinical tools in the pipeline.
The core strength of our offering comes from the fact that our tools are designed by pathologists, for pathologists.
Our expert science team, made up of clinical pathologists and scientists from various areas, works together closely with our software developers to design solutions created with the end-user in mind.
We also work closely with partners like the Mayo Clinic to design bespoke services and solutions to fit their needs. We pride ourselves in seamlessly adapting to these differing needs.
Some of Aiforia’s products utilize a cloud-based platform, a technology not often seen in the medical sector. Do you think with a rise in AI-based technologies in the healthcare sector, cloud-based platforms will become commonplace? What advantages would this bring to the sector?
Cloud-based software, especially in pathology, is vital for many reasons. Aiforia’s cloud platform enables pathologists to: scale their work with unparalleled computing power, store images and data securely, work and collaborate flexibly with remote access, integrate without any restrictions, and to automatically access the latest updates and features of our software.
Remote collaboration and work is something I want to highlight. It removes the need for pathologists and labs to mail physical slides, unbinds them from microscopes and labs, and enables pathologists to store these enormous file sizes that glass slides make up when digitized.
Considering the impact a technology has on not only the pathologist, but the lab and the patient involved, is crucial for success. How does Aiforia approach taking this holistic view when designing products? How do solutions balance the benefits for each party?
I believe that our solutions inevitably benefit all, from pathologists to the labs they are working in, and of course, the patient. As I mentioned earlier, AI-assisted diagnostics harbors many benefits. Our solutions are designed to help pathologists easily reap those benefits from assisting in their work and enabling precision diagnostics.
Patients can receive diagnoses faster, are administered personalized treatments, and care is democratized. In turn, the benefit to the hospital is the increased output, meaning more cases are analyzed in less time, enhanced staff satisfaction, and cost savings.
© Aiforia Technologies Plc
Aiforia offers support for both clinical and preclinical settings. What are the key differences between the products offered for these two applications?
The value creation that Aiforia’s solutions provide between the two industries, preclinical and clinical, is uniform: increasing the speed, accuracy, and consistency of image analysis. This creates value for the individual, the organization, and the healthcare industry as a whole through the discovery of new prognostic markers for illnesses, the production of novel molecules to treat disease, and so on.
In your opinion, what are the major challenges that limit the advancement of digitalization within the healthcare sector and how might they be overcome?
The digital transformation in pathology is well underway. The digitization of glass slides traditionally examined under a microscope can now be analyzed on a computer, which is becoming increasingly prevalent in labs and hospitals worldwide to modernize diagnostic workflows.
The importance of this digital transformation has been further strengthened as a result of the COVID-19 pandemic. Meanwhile, that digitization of course has paved the way for even more poweful technology like AI to be adopted.
A recent survey with pathologists reported that 75% of the respondents, expressed an interest or excitement in using AI as a diagnostic tool to facilitate improvements in workflow efficiency.
What do the next ten years look like for Aiforia? Are there any innovations or sectors you are striving towards?
We are well underway in entering the clinical diagnostics market and aim to have several CE-IVD marked clinical AI models for diagnostic support. We already have our CE-IVD marked models for breast and lung cancer diagnostics.
In the pipeline, we also have the Aiforia Clinical Suites for some of the world’s most prevalent cancers. Each Clinical Suite is a portfolio of AI-powered and automated tools which can be easily deployed in a clinical pathology lab, integrating into existing lab setups.
We will continue to strengthen our presence in the preclinical market with a particular focus on the pharmaceutical industry. Some of the world’s biggest pharmaceutical companies like Boehringer Ingelheim and Sanofi, are already our customers.
We aim to increase the number of these partnerships while continuing to develop and commercialize more tools for preclinical analysis.
About Jukka Tapaninen
Jukka has held various executive positions over the past 25 years in international IT and software businesses such as SAP and HP. Some of the wealth of experience includes: leading enterprise software sales for healthcare industries as well as overseeing global business development, building strategic partnerships and scaling-up growth companies.