Jeff Elton, Ph.D., is CEO of ConcertAI, an AI SaaS options firm offering analysis options and patient-centric options for all times sciences innovators and the world’s main suppliers. ConcertAI is concentrated on accelerating and bettering the precision of retrospective and potential medical research utilizing supplier EMRs, LISs, and PACSs programs because the supply for all research knowledge. It’s a long-term companion companion with the American Society of Scientific Oncology and its CancerLinQ program, US FDA, NCI Well being Fairness initiatives, and nearly 100 healthcare suppliers throughout the US.
Previous to ConcertAI, Jeff was Managing Director, Accenture Technique/Affected person Well being; International Chief Working Officer and SVP Technique at Novartis Institutes of BioMedical Analysis, Inc.; and companion at McKinsey & Firm. He’s additionally a founding board member and senior advisor to a number of early-stage firms. Jeff is presently a board member of the Massachusetts Biotechnology Council. He’s the co-author of the extensively cited e book, Healthcare Disrupted (Wiley, 2016). Jeff has a Ph.D. and M.B.A. from The College of Chicago.
Because the founding CEO of ConcertAI, are you able to share your imaginative and prescient for the corporate at its inception? How has that imaginative and prescient advanced since 2018?
We began with the concept that improved affected person outcomes come from deep and actionable insights. Gaining these insights requires knowledge completeness, knowledge scale, knowledge representativeness and superior AI intelligence. So, we created a Information-as-a-Service and AI Software program-as-a-Service firm. We focused AI that enables inferencing and prediction. This included predicting occasions to keep away from, equivalent to sufferers’ non-adherence to their remedy or discontinuation of care due to a scarcity of optimistic response, which knowledgeable when medical trials is perhaps the subsequent possibility.
Our imaginative and prescient has remained steadfast, and we proceed to count on extra out of our options. With the most recent technology of LLMs, agentic AI and different generative AI options, we will function at scale (and nearly in real-time—one thing we didn’t count on or anticipate in 2018). With companions like NVIDIA, we will advance our options to carry out higher than anticipated, acknowledge limitations and distinctive traits, and transfer on the tempo of your entire market’s improvements—the journey thus far has been terribly productive and exhilarating.
We now have opened up beforehand unimaginable efficiency in medical trial automation options, automating the position of sufferers on evidence-based medical pathways, superior workflows in radiological interpretation, and using digital twins as a decision-enhancing software for care and analysis.
At present, we serve nearly 50 biopharma innovators and a couple of,000 healthcare suppliers—so whereas not at fairly the size of your entire market, we’re the broadest-reaching AI options for oncology within the trade.
What impressed you to give attention to oncology and hematology datasets particularly, and the way did you see ConcertAI making a distinction in these fields?
The USA began the “Conflict on Most cancers” in 1971 with the Nationwide Most cancers Act. This catalyzed large-scale authorities funding, which generated insights into the mutations that drive cancers, new modalities for therapies, expanded Nationwide Most cancers Institute-designated therapy facilities, and extra. Beneath the Obama administration, funding elevated once more by $10 billion in digital stimulus going to the NIH and, in flip, to the NCI. Beneath Biden, the Most cancers Moonshot 2.0 program was launched in 2022, once more catalyzing a wholly new technology of analysis and seed funding funding for educational, group, and private-public partnerships.
I give this historical past as a result of few ailments or areas of healthcare have the extent of information: genomic, transcriptomic, digital pathology, digital radiology, detailed digital medical data, and so on., and the extent of analysis that contextualizes these knowledge with validated insights by means of rigorous, multi-center, peer-review research. As additional proof, the American Society of Scientific Oncology annual assembly is the biggest medical assembly on the planet, with the best variety of new publications, posters and abstracts of any scientific discussion board on any matter.
So, if you’ll be knowledge and AI-centric, there are few higher areas to advance options with confidence and at scale than oncology. ConcertAI has the biggest assortment of research-grade knowledge of anybody on the planet. It consists of lots of of peer-reviewed publications enabled by that knowledge, vital proof ensuing from these publications altering how sufferers are handled and assuring probably the most optimistic doable outcomes, and now AI SaaS applied sciences which might be integral to the processes of care and analysis that convey the facility of that knowledge and proof to bear in any respect factors and for all selections alongside a affected person’s care journey. What is basically vital right here is that we don’t do that unilaterally. It’s finished transparently with our healthcare supplier and biopharma innovator companions to engender the best confidence and use. So, we’re evolving towards real-time, superior, AI intelligence-enabled choice augmentation.
ConcertAI has develop into a number one participant in real-world proof (RWE) and AI expertise for healthcare. What had been among the early challenges you confronted in positioning the corporate as a frontrunner on this area?
It’s important to be trusted and evolve in direction of being the reference supply. That’s earned. The belief comes out of your supplier companions, believing that the info you’re accessing is in the most effective pursuits of their sufferers. Belief comes out of your tutorial and trade companions, who see the proof of and imagine that your knowledge is derived as an ideal reflection of the unique affected person data and that the ideas you advance are ‘true’ and reflective of present medical and scientific observe. You even have to realize a scale that your knowledge options characterize not solely your entire inhabitants but additionally produce conclusions which might be confidently generalizable again to the total inhabitants being handled with a selected medication. Know-how is comparable. Scientists and clinicians are inherently skeptical—as they need to be—and don’t belief black bins or algorithms they don’t perceive. So we would have liked to ascertain belief there, too, by means of publications and being open about how our options work.
ConcertAI holds the world’s largest oncology and hematology dataset. What distinctive alternatives does this knowledge create for reworking most cancers analysis and therapy?
I like that query. We’re engaged on this on daily basis! The alternatives to offer worth to suppliers, sufferers and innovators are nearly limitless. In early-phase trials, we’re evolving research simulation approaches with digital twins that can change the packages we take into medical trials. Our knowledge and AI optimizations will decrease the time required to go from finalized protocol to finalized submission to regulators by 30 to 40%—which means new medicines get to sufferers sooner. Our choice augmentation AI options will suggest pathways for therapy which might be evidence-based and particularly tailor-made to these pathways, monitor responses consistent with the anticipated response, and search for probably helpful medical trials when response or profit is under expectations. Our imaging medical interpretation options function on the stage of operational processes, medical interpretation, and longer-term view of recent interpretations or new interventions that needs to be thought of based mostly on insights and proof sooner or later. Not is an motion “as soon as and finished” however relatively it turns into “as soon as, after which repeatedly” such that helpful reassessments and future selections are an ongoing course of! What’s completely different right here is that the view is your entire affected person journey—it is a horizontal view versus a collection of slim, deep, vertical views that need to be stitched collectively. That is an innovation enabled by AI and a profound course of change that gives new methods of working to the knowledgeable people concerned.
Are you able to clarify how ConcertAI’s Digital Trial Answer works to match most cancers sufferers with life-saving medical trials? What impression have you ever seen thus far when it comes to affected person outcomes?
Scientific trials are very complicated and require hours of effort by a variety of extremely knowledgeable people. For many organizations, medical trials are provided as a duty and dedication to sufferers the place the present commonplace of care could not characterize a viable various. Trials have not likely been very accessible to sufferers in group therapy facilities, the place 80% of sufferers obtain their care. But, these are the sufferers who will finally be receiving newly authorized medicines. This creates a double dilemma: nearly all of sufferers who want entry to trials are restricted, and those that are reflective of the last word commonplace of care inhabitants are usually not within the trial dataset. We set a path to resolve these issues.
The outcomes have been nice—so optimistic that we’re going to be increasing our variety of research underway by 10x in 2025. We printed this for the final American Society of Scientific Oncology conferences and in different areas. Our method is how we expect AI needs to be applied—as an augmentation of knowledgeable people the place there are massive capability and expertise constraints and the place lives are at stake. We now have developed a set of orchestrated and tuned massive language fashions that entry affected person data, synthesize traits, and match sufferers to probably helpful trials, doing precisely what the knowledgeable people would do—with a completely documented method to creating suggestions and assessments. Within the websites the place our applied sciences are deployed, we carry out on the stage of probably the most knowledgeable people and accrue sufferers at 5x or extra relative to websites the place our applied sciences are usually not deployed—the analysis groups and biopharma innovators are each happy, and sufferers profit most.
How does ConcertAI’s AI-driven method to trial design and affected person recruitment handle among the present limitations in medical analysis, equivalent to affected person range and trial effectivity?
I’m pleased with my workforce—they instructed me three to 4 years in the past that reaching range is an obligation and the correct factor to do scientifically. Additionally they maintained that it’s exhausting to do whether it is guide however requires zero incremental effort if automated. So, we determined then that each dataset and AI SaaS answer would combine range and social determinants of well being traits as our commonplace method. It’s not an possibility. It’s simply what we do. Subsequently, our CARAai™ supported medical trial design and optimization options can assess what ethnic, racial or financial subpopulations could also be most adversely impacted by a illness, combine these issues into the trial design, make sure that these populations are usually not unwittingly excluded, and outline the medical websites almost definitely to guarantee participation and representativeness. That is the place AI could be “AI for Good” and the place expertise doesn’t introduce a bias however assures that biases don’t enter the method, the last word design, or the operational processes across the medical trial.
What position does ConcertAI play in lowering the burden on healthcare suppliers and optimizing website choice in medical trials?
We combine the work burden into all features of our medical trial options. First, there’s a burden on the affected person. This may be the place the location is situated, the variety of visits required for a research versus the usual of care, or the medical depth of a research versus the usual of care, as within the case of further biopsies. This stuff can decide whether or not the affected person—or the affected person in session with their supplier—can afford to take part or tolerate and full participation.
There may be additionally a burden on the supplier. If we will automate the identification of sufferers for medical trial eligibility, decrease false positives that create work, and supply what we name “AI leverage” to the work of the Scientific Analysis Related, Research Nurses, and Physicians, then the burden is lowered. The identical is true of our AI Automation Answer, which permits the analysis workforce to keep away from doing guide knowledge entry—usually 2 to 4 hours on the finish of the day, and sometimes accomplished at dwelling. Early on we seemed on the knowledge within the EMR—digital—being manually entered right into a portal for the sponsor’s EDC. So digital knowledge is being learn after which rekeyed to develop into digital knowledge once more! Right here, too, we’re utilizing our multi-tuned massive language fashions—this was an actual focus of the NVIDIA partnership from the start. We’re at 55% full automation right this moment, with a really quick path to over 80% within the coming few months. As these parts come collectively, we’ll get the employees time all the way down to 10% of legacy necessities and make these research extra accessible to extra sufferers.
Precision medication is a key space the place AI is making vital strides. How does ConcertAI’s expertise contribute to extra exact and personalised most cancers remedies?
We’ve not mentioned this an excessive amount of since final 12 months. In December 2023, we assumed duty for the American Society of Scientific Oncology’s (ASCO) CancerLinQ program. It’s the world’s largest clever well being community, comprising tutorial facilities, regional hospital programs and group suppliers. A key a part of this community is implementing the ASCO Licensed® high quality and medical pathway options. Since CancerLinQ is a ConcertAI initiative, we have now been rising the community, automating precision oncology pathways, creating new digital twin approaches for augmenting therapy choice for the suppliers, figuring out and messaging crucial diagnostic exams that would inform therapy selections, and doing the identical for newly authorized medicines that characterize one other or higher therapy various. All of that is underpinned by our CARAai™ structure, once more a set of imaginative and prescient LLM and tuned oncology LLMs finished in collaboration with NVIDIA. It’s superb to see the progress being made, and we’re enthusiastic about what we’ll be publishing and presenting at subsequent 12 months’s ASCO 2025.
How do you see AI imaging options benefiting fields like oncology and radiology, particularly as these fields face clinician shortages?
Nice query! It’s true that each the variety of new oncologists and radiologists coming into the sphere is lower than the quantity retiring. Nevertheless, affected person demand is ever-increasing. So, it’s the preferrred space for offering AI SaaS options that help doctor and allied care professionals in each workflow optimization and medical choice augmentation. Radiologists and oncologists will each cite the significance of those new clever options coming into their fields particularly. Imaging is an excellent space for AI, and its efficiency is outstanding. Non-inferiority research replicate that AI fashions could be near or similar to knowledgeable people in slim areas. Orchestrated workflows can convey this all collectively. The identical is true in oncology, the place we’re bringing collectively molecular take a look at outcomes with immune response knowledge, predictive algorithms for resistance and different parts that can all inform the therapy choice and allow response monitoring. I’ve been within the subject for years and on completely different sides of recent improvements—what we will do now could be effectively past something we had been ever capable of do earlier than, and the tempo of change is superb.
As an skilled chief in healthcare expertise, what recommendation would you supply to new firms trying to make a significant impression in healthcare by means of AI?
You may’t be an AI firm with out entry to knowledge at scale. Information is the substrate for constructing coaching and monitoring fashions. Additionally, constructing AI options is a workforce sport. You want area data at an distinctive depth matched with a brand new technology of AI mannequin growth capabilities that acknowledges the behaviors of various courses of AI options and might convey them to bear towards slim targets, particularly tuned for human or above efficiency. Then, these approaches could be orchestrated in varied methods to characterize a brand new system for working—that’s the place the adjustments happen, and the worth will get delivered. Observe “AI Humility” as every little thing is superb and reveals issues we couldn’t do even six months earlier than. But, ‘superb’ isn’t essentially a product or a brand new approach of working—it’s simply that, expertise doing one thing new. It’s the duty of the AI firm to make it a brand new approach of working and a brand new method for delivering an astonishing stage of worth that was by no means accessible earlier than. Lastly, assume that you must show belief in enterprise practices, AI fashions, and answer transparency. We’re nonetheless early in our societal journey, and we’re those who need to earn the belief to convey concerning the adjustments we’re able to delivering.
Thanks for the good interview, readers who want to study extra ought to go to ConcertAI.