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 bettering the precision of retrospective and potential medical research utilizing supplier EMRs, LISs, and PACSs programs because the supply for all research information. It’s a long-term accomplice accomplice with the American Society of Medical 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; International Chief Working Officer and SVP Technique at Novartis Institutes of BioMedical Analysis, Inc.; and accomplice at McKinsey & Firm. He’s additionally a founding board member and senior advisor to a number of early-stage corporations. Jeff is at the moment a board member of the Massachusetts Biotechnology Council. He’s the co-author of the broadly cited ebook, 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 information completeness, information scale, information 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 permits inferencing and prediction. This included predicting occasions to keep away from, corresponding to sufferers’ non-adherence to their remedy or discontinuation of care due to a scarcity of optimistic response, which knowledgeable when medical trials could be the following possibility.
Our imaginative and prescient has remained steadfast, and we proceed to anticipate extra out of our options. With the most recent technology 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 your complete market’s improvements—the journey thus far has been terribly productive and exhilarating.
We have now 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 the usage of digital twins as a decision-enhancing software for care and analysis.
At this time, we serve virtually 50 biopharma innovators and a pair of,000 healthcare suppliers—so whereas not at fairly the size of your complete market, we’re the broadest-reaching AI options for oncology within the business.
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 US began the “Warfare 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 wholly new technology of analysis and seed funding funding for tutorial, group, and private-public partnerships.
I give this historical past as a result of few ailments or areas of healthcare have the extent of knowledge: genomic, transcriptomic, digital pathology, digital radiology, detailed digital medical information, and many others., and the extent of analysis that contextualizes these information with validated insights by means of rigorous, multi-center, peer-review research. As additional proof, the American Society of Medical Oncology annual assembly is the biggest medical assembly on this 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 information 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 information of anybody on this planet. It contains a whole bunch of peer-reviewed publications enabled by that information, important proof ensuing from these publications altering how sufferers are handled and assuring essentially the most optimistic attainable outcomes, and now AI SaaS applied sciences which might be integral to the processes of care and analysis that carry the ability of that information and proof to bear in any respect factors and for all selections alongside a affected person’s care journey. What is admittedly vital right here is that we don’t do that unilaterally. It’s executed 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 have been among the early challenges you confronted in positioning the corporate as a pacesetter on this area?
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 information you’re accessing is in one of the best pursuits of their sufferers. Belief comes out of your educational and business companions, who see the proof of and imagine that your information is derived as an ideal reflection of the unique affected person information and that the ideas you advance are ‘true’ and reflective of present medical and scientific apply. You even have to realize a scale that your information options symbolize not solely your complete inhabitants but in addition produce conclusions which might be confidently generalizable again to the total inhabitants being handled with a selected drugs. 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 information 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 research simulation approaches with digital twins that may change the packages we take into medical trials. Our information and AI optimizations will decrease the time required to go from finalized protocol to finalized submission to regulators by 30 to 40%—that 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 in keeping with the expected response, and search for doubtlessly useful 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 primarily based on insights and proof sooner or later. Not is an motion “as soon as and executed” however relatively it turns into “as soon as, after which repeatedly” such that useful reassessments and future selections are an ongoing course of! What’s totally different right here is that the view is your complete affected person journey—this can be a horizontal view versus a collection of slender, 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 Answer works to match most cancers sufferers with life-saving medical trials? What impression have you ever seen thus far by way of affected person outcomes?
Medical trials are very complicated 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 commonplace of care might 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 finally be receiving newly authorised medicines. This creates a double dilemma: nearly all of sufferers who want entry to trials are restricted, and people who are reflective of the final word commonplace of care inhabitants should 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 Medical Oncology conferences and in different areas. Our strategy 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 have now developed a set of orchestrated and tuned giant language fashions that entry affected person information, synthesize traits, and match sufferers to doubtlessly useful trials, doing precisely what the skilled people would do—with a completely documented strategy to creating suggestions and assessments. Within the websites the place our applied sciences are deployed, we carry out on the degree of essentially the most skilled people and accrue sufferers at 5x or extra relative to websites the place our applied sciences should not deployed—the analysis groups and biopharma innovators are each happy, and sufferers profit most.
How does ConcertAI’s AI-driven strategy to trial design and affected person recruitment deal with among the present limitations in medical analysis, corresponding to affected person variety and trial effectivity?
I’m happy with my workforce—they advised me three to 4 years in the past that reaching variety is an obligation and the appropriate factor to do scientifically. In addition they maintained that it’s onerous 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 variety and social determinants of well being traits as our commonplace strategy. 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 concerns into the trial design, be sure that these populations should not unwittingly excluded, and outline the medical websites most definitely to guarantee participation and representativeness. That is the place AI may be “AI for Good” and the place know-how doesn’t introduce a bias however assures that biases don’t enter the method, the final word design, or the operational processes across the medical trial.
What position does ConcertAI play in decreasing the burden on healthcare suppliers and optimizing web site choice in medical trials?
We combine the work burden into all facets of our medical trial options. First, there’s a burden on the affected person. This may be the place the positioning is positioned, 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. 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’s 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 Medical Analysis Related, Examine 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 handbook information entry—usually 2 to 4 hours on the finish of the day, and sometimes accomplished at residence. Early on we regarded on the information within the EMR—digital—being manually entered right into a portal for the sponsor’s EDC. So digital information is being learn after which rekeyed to grow to be digital information 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 immediately, 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 drugs is a key space the place AI is making important strides. How does ConcertAI’s know-how contribute to extra exact and customized 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 Medical Oncology’s (ASCO) CancerLinQ program. It’s the world’s largest clever well being community, comprising educational 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 now have been rising the community, automating precision oncology pathways, creating new digital twin approaches for augmenting remedy choice for the suppliers, figuring out and messaging essential diagnostic exams that might inform remedy selections, 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 executed 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 coming into the sphere is lower than the quantity retiring. Nonetheless, affected person demand is ever-increasing. So, it’s the perfect 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 phenomenal. Non-inferiority research mirror that AI fashions may be near or similar to skilled people in slender areas. Orchestrated workflows can carry this all collectively. The identical is true in oncology, the place we’re bringing collectively molecular check outcomes with immune response information, predictive algorithms for resistance and different parts that may all inform the remedy choice and allow response monitoring. I’ve been within the area for years and on totally different sides of latest improvements—what we are able to do now could be properly past something we have been ever capable of do earlier than, and the tempo of change is wonderful.
As an skilled chief in healthcare know-how, what recommendation would you provide to new corporations seeking to make a significant impression in healthcare by means of AI?
You possibly can’t be an AI firm with out entry to information at scale. Knowledge 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 lessons of AI options and may carry them to bear towards slender goals, particularly tuned for human or above efficiency. Then, these approaches may be orchestrated in varied methods to symbolize a brand new system for working—that’s the place the adjustments happen, and the worth will get delivered. Follow “AI Humility” as all the pieces is wonderful and displays issues we couldn’t do even six months earlier than. But, ‘wonderful’ shouldn’t be essentially a product or a brand new approach 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 approach of working and a brand new strategy for delivering an astonishing degree of worth that was by no means accessible earlier than. Lastly, assume it is advisable to reveal 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 in regards to the adjustments we’re able to delivering.
Thanks for the nice interview, readers who want to study extra ought to go to ConcertAI.
