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 targeted on accelerating and enhancing the precision of retrospective and potential medical research utilizing supplier EMRs, LISs, and PACSs programs because the supply for all examine knowledge. It’s a long-term associate associate with the American Society of Scientific Oncology and its CancerLinQ program, US FDA, NCI Well being Fairness initiatives, and virtually 100 healthcare suppliers throughout the US.
Previous to ConcertAI, Jeff was Managing Director, Accenture Technique/Affected person Well being; World Chief Working Officer and SVP Technique at Novartis Institutes of BioMedical Analysis, Inc.; and associate at McKinsey & Firm. He’s additionally a founding board member and senior advisor to a number of early-stage firms. Jeff is at present 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 developed 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 Knowledge-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, resembling sufferers’ non-adherence to their remedy or discontinuation of care due to a scarcity of constructive response, which knowledgeable when medical trials could be the following choice.
Our imaginative and prescient has remained steadfast, and we proceed to anticipate extra out of our options. With the newest era of LLMs, agentic AI and different generative AI options, we are able to function at scale (and virtually in real-time—one thing we didn’t anticipate or anticipate in 2018). With companions like NVIDIA, we are able to advance our options to carry out higher than anticipated, acknowledge limitations and distinctive traits, and transfer on the tempo of all the market’s improvements—the journey to this point 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.
Immediately, we serve virtually 50 biopharma innovators and a pair of,000 healthcare suppliers—so whereas not at fairly the dimensions of all the market, we’re the broadest-reaching AI options for oncology within the trade.
What impressed you to concentrate on oncology and hematology datasets particularly, and the way did you see ConcertAI making a distinction in these fields?
The USA began the “Struggle 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 remedy 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 completely new era of analysis and seed funding funding for tutorial, group, and private-public partnerships.
I give this historical past as a result of few illnesses or areas of healthcare have the extent of knowledge: 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 via rigorous, multi-center, peer-review research. As additional proof, the American Society of Scientific Oncology annual assembly is the most important 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’re going to be knowledge and AI-centric, there are few higher areas to advance options with confidence and at scale than oncology. ConcertAI has the most important assortment of research-grade knowledge of anybody on the planet. It contains lots of of peer-reviewed publications enabled by that knowledge, important proof ensuing from these publications altering how sufferers are handled and assuring probably the most constructive doable outcomes, and now AI SaaS applied sciences which might be integral to the processes of care and analysis that carry the facility of that knowledge and proof to bear in any respect factors and for all choices alongside a affected person’s care journey. What is admittedly essential 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 grow to be a number one participant in real-world proof (RWE) and AI know-how for healthcare. What had been among the early challenges you confronted in positioning the corporate as a frontrunner on this house?
You need 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 might be accessing is in the perfect 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 apply. You even have to attain a scale that your knowledge options symbolize not solely all the inhabitants but additionally produce conclusions which might be confidently generalizable again to the total inhabitants being handled with a specific drugs. Expertise is analogous. Scientists and clinicians are inherently skeptical—as they need to be—and don’t belief black packing containers or algorithms they don’t perceive. So we would have liked to ascertain belief there, too, via 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 remedy?
I like that query. We’re engaged on this day by day! The alternatives to offer worth to suppliers, sufferers and innovators are virtually limitless. In early-phase trials, we’re evolving examine simulation approaches with digital twins that can change the applications 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 quicker. Our choice augmentation AI options will advocate pathways for remedy which might be evidence-based and particularly tailor-made to these pathways, monitor responses according to the expected response, and search for doubtlessly helpful medical trials when response or profit is beneath expectations. Our imaging medical interpretation options function on the degree of operational processes, medical interpretation, and longer-term view of latest interpretations or new interventions that ought to be thought of based mostly on insights and proof sooner or later. Now not is an motion “as soon as and finished” however relatively it turns into “as soon as, after which many times” such that helpful reassessments and future choices are an ongoing course of! What’s totally different right here is that the view is all the affected person journey—this can be a horizontal view versus a sequence of slim, deep, vertical views that must be stitched collectively. That is an innovation enabled by AI and a profound course of change that gives new methods of working to the skilled people concerned.
Are you able to clarify how ConcertAI’s Digital Trial Resolution works to match most cancers sufferers with life-saving medical trials? What influence have you ever seen to this point by way of affected person outcomes?
Scientific trials are very advanced and require hours of effort by a variety of extremely skilled people. For many organizations, medical trials are supplied as a accountability and dedication to sufferers the place the present normal of care could not symbolize a viable various. Trials have probably not been very out there to sufferers in group remedy facilities, the place 80% of sufferers obtain their care. But, these are the sufferers who will in the end be receiving newly authorised medicines. This creates a double dilemma: the vast majority of sufferers who want entry to trials are restricted, and people who are reflective of the last word normal of care inhabitants aren’t within the trial dataset. We set a path to resolve these issues.
The outcomes have been nice—so constructive that we’re going to be increasing our variety of research underway by 10x in 2025. We revealed this for the final American Society of Scientific Oncology conferences and in different areas. Our method is how we predict AI ought to be carried out—as an augmentation of skilled people the place there are giant capability and expertise constraints and the place lives are at stake. We now have developed a set of orchestrated and tuned giant language fashions that entry affected person data, synthesize traits, and match sufferers to doubtlessly helpful trials, doing precisely what the skilled people would do—with a totally documented method to creating suggestions and assessments. Within the websites the place our applied sciences are deployed, we carry out on the degree of probably the most skilled people and accrue sufferers at 5x or extra relative to websites the place our applied sciences aren’t 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 tackle among the present limitations in medical analysis, resembling affected person range and trial effectivity?
I’m happy with my staff—they instructed me three to 4 years in the past that attaining range is an obligation and the suitable factor to do scientifically. In addition they maintained that it’s laborious to do whether it is handbook 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 normal method. It’s not an choice. 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 concerns into the trial design, make sure that these populations aren’t unwittingly excluded, and outline the medical websites more than likely to guarantee participation and representativeness. That is the place AI could be “AI for Good” and the place know-how 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 function does ConcertAI play in lowering the burden on healthcare suppliers and optimizing web site 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 positioning is situated, the variety of visits required for a examine versus the usual of care, or the medical depth of a examine versus the usual of care, as within the case of further biopsies. These items 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 are able to automate the identification of sufferers for medical trial eligibility, reduce false positives that create work, and supply what we name “AI leverage” to the work of the Scientific Analysis Related, Examine Nurses, and Physicians, then the burden is lowered. The identical is true of our AI Automation Resolution, which permits the analysis staff to keep away from doing handbook knowledge entry—usually 2 to 4 hours on the finish of the day, and infrequently accomplished at house. Early on we appeared 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 grow to be digital knowledge once more! Right here, too, we’re utilizing our multi-tuned giant language fashions—this was an actual focus of the NVIDIA partnership from the start. We’re at 55% full automation right now, with a really quick path to over 80% within the coming few months. As these parts come collectively, we’ll get the workers time right down to 10% of legacy necessities and make these research extra accessible to extra sufferers.
Precision drugs is a key space the place AI is making important strides. How does ConcertAI’s know-how contribute to extra exact and personalised most cancers therapies?
We’ve not mentioned this an excessive amount of since final 12 months. In December 2023, we assumed accountability 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’ve been rising the community, automating precision oncology pathways, creating new digital twin approaches for augmenting remedy choice for the suppliers, figuring out and messaging crucial diagnostic checks that would inform remedy choices, and doing the identical for newly authorised medicines that symbolize one other or higher remedy 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 wonderful 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 getting into the sector is lower than the quantity retiring. Nonetheless, affected person demand is ever-increasing. So, it’s the excellent 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 a superb space for AI, and its efficiency is phenomenal. Non-inferiority research mirror that AI fashions could be near or similar to skilled people in slim areas. Orchestrated workflows can carry 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 remedy choice and allow response monitoring. I’ve been within the subject for years and on totally different sides of latest improvements—what we are able to do now could be nicely past something we had been ever in a position to do earlier than, and the tempo of change is wonderful.
As an skilled chief in healthcare know-how, what recommendation would you supply to new firms seeking to make a significant influence in healthcare via AI?
You possibly can’t be an AI firm with out entry to knowledge at scale. Knowledge is the substrate for constructing coaching and monitoring fashions. Additionally, constructing AI options is a staff sport. You want area data at an distinctive depth matched with a brand new era of AI mannequin improvement capabilities that acknowledges the behaviors of various courses of AI options and might carry them to bear towards slim targets, particularly tuned for human or above efficiency. Then, these approaches could be orchestrated in numerous methods to symbolize a brand new system for working—that’s the place the modifications happen, and the worth will get delivered. Observe “AI Humility” as all the things is wonderful and displays issues we couldn’t do even six months earlier than. But, ‘wonderful’ isn’t essentially a product or a brand new manner of working—it’s simply that, know-how doing one thing new. It’s the accountability of the AI firm to make it a brand new manner of working and a brand new method for delivering an astonishing degree of worth that was by no means accessible earlier than. Lastly, assume you want to exhibit belief in enterprise practices, AI fashions, and answer transparency. We’re nonetheless early in our societal journey, and we’re those who must earn the belief to carry concerning the modifications we’re able to delivering.
Thanks for the nice interview, readers who want to study extra ought to go to ConcertAI.