I met ARTIDIS co-founders Marija Plodinec Ph.D. and Dr. Marko Loparic in 2019 when they were participating in Accelerator for HealthTech. Since the company has opened up its US headquarters in the Innovation Factory and initiated several collaborations across Texas Medical Center institutions. I sat down with Marija to discuss her founder’s journey, successfully launching clinical trials, and AI.
Who are you and what inspired you to start your company?
It was a serendipitous Roche fellowship that brought me to Switzerland. During my doctorate, I discovered the nanomechanical signature of breast cancer and was inspired to leverage my background in physics in oncology. This revelation led me to collaborate with Dr. Marko Loparic, Philipp Oertle, and Tobias Appenzeller, and together we launched ARTIDIS AG. We got our footing at the University of Basel with our first successful prospective study that recruited 545 patients. Since then, we participated in TMCi Accelerator for HealthTech and initiated strategic alliances within the world’s leading cancer centers including MD Anderson Cancer Center. This would not be possible without cultivating a diverse team of 60+ experts from over 25 nations.
Tell our readers about ARTIDIS’ vision.
We are on a mission to shift the paradigm of cancer care from central lab to patient bedside. ARTIDIS diagnoses cancer, detects its aggressiveness, and predicts the probability of a patient developing metastases based on the nanomechanical signature for cancer in under an hour. We envision being the standard of care for tissue analysis and therapy optimization bringing benefits to patients, clinicians, and the healthcare system.
What have been the easiest and most challenging parts of being a founder?
I am inspired by the perseverance of cancer patients and the evolution of technology in oncology – it fuels me day in and day out. There is an ease to the work we do because we as a company have been touched by cancer in one way or another, it motivates us on a personal level. Scaling a business in healthcare takes vision, stamina, compliance, and most importantly a group of talented individuals who have complementary qualities – this is how we’ve grown ARTIDIS. Launching strategic alliances across Europe, North America, and Asia takes a team dedicated to excellence – finding and keeping employees engaged isn’t a challenge, it’s an opportunity to find people with a shared vision. I’m proud of how ARTIDIS has kept our culture intact through difficult times like the pandemic, economic crisis, and exponential growth because we invested in people through professional development, consistent 1:1’s, and leading with emotional intelligence.
Many HealthTech companies aim to stay patient-centric while figuring out the nuances of integrating into the clinical workflow. What advice do you have for them?
Patient advocacy has been at the heart of my work since my Ph.D. studies and continues to be a part of my life. My biggest advice is to listen. We did this from the beginning, first, we mapped out the clinical process, then we got clear what the patient is experiencing as a part of the clinical workflow. Form questions that help your organization get to know the perspectives, interests, and workflow of all stakeholders. Then, engage with patients as you build out different facets of your company. From clinical trials to communication materials, ask for their feedback. Our clinical operations team considers themselves the bridge between patients and physicians, translating science for effective cancer care while maintaining respect for existing clinical workflow.
Your company has designed several clinical trials, what advice do you have for other founders preparing for this step?
Keep in mind the slightest adjustment to workflow requires a change in mindset and culture. There are financial, cultural, and technological barriers to overcome. Your leadership should encourage incorporating trials into clinical treatment pathways and clinical decision support systems when appropriate so that trials are considered an option.
We are on the verge of a new era of cancer care. From your perspective what technologies are shaping the future of oncology?
It is an exciting time to be innovating in oncology. From my perspective technologies that address the tumor, and its microenvironment are shaping the future of precision diagnostics and optimized treatment plans for cancer patients. The evolution of OMICS progressed oncology, but it’s not enough, the composition and functional state of the microenvironment plays a crucial role in enhancing chemotherapy and radiotherapy efficacy. We’ve developed a novel imaging modality that brings subcellular resolution to tissue analysis at patient’s bedside. The nanomechanical imaging informs the tissue phenotype, the sum of functional properties of different tissue components like cells, matrix, and immune landscape. This new era of cancer care includes many targeted therapies that affect tumor microenvironment, this creates a need for an advancement in diagnosis that can support much better outcomes than we have today, which land in the range of 10-20% for targeted patient groups.
How do you think the integration of AI into current cancer detection methods will affect patient outcomes and overall healthcare costs?
AI is already an integral part of the read-out process in radiology, assisting physicians in quantifying and understanding imaging data. Right now, 80% of patients who undergo breast biopsy after positive imaging results do not have cancer, these false positives create unnecessary costs for healthcare and emotional costs for the patient. There is room to improve this integration by taking a longitudinal approach. Within our digital platform, we combine actual measurements with data analytics that takes into account clinical patient information that is integrative and comprehensive, this optimizes the treatment plan for patients and minimizes overall healthcare costs.
How can we ensure that AI algorithms for cancer detection are fair and unbiased, and what steps are being taken to address potential algorithmic biases?
The core of the problem comes from bias that arises during data collection this usually begins with clinical trials. From how the trials are incentivized and designed, we need a top-down approach that starts with regulatory agencies to push for diversity and inclusion. Thinking about facets like data completeness, test case preparation, data de-biasing, fairness checking, end-user feedback, and continuous monitoring is the best way to address potential biases. However, if the regulators don’t enforce and payers do not support it, we won’t see the change, not just in AI, but in broader healthcare.