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 scientific research utilizing supplier EMRs, LISs, and PACSs techniques because the supply for all examine information. It’s a long-term associate associate with the American Society of Medical 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; 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 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 Information-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, equivalent to sufferers’ non-adherence to their remedy or discontinuation of care due to a scarcity of optimistic response, which knowledgeable when scientific trials may be the subsequent choice.
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 are able to function at scale (and nearly in real-time—one thing we didn’t count on 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 entire market’s improvements—the journey to this point has been terribly productive and exhilarating.
We’ve opened up beforehand unimaginable efficiency in scientific trial automation options, automating the location of sufferers on evidence-based scientific pathways, superior workflows in radiological interpretation, and the usage of digital twins as a decision-enhancing device for care and analysis.
At present, we serve nearly 50 biopharma innovators and a pair 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 “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. Underneath the Obama administration, funding elevated once more by $10 billion in digital stimulus going to the NIH and, in flip, to the NCI. Underneath 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 illnesses or areas of healthcare have the extent of information: genomic, transcriptomic, digital pathology, digital radiology, detailed digital medical information, and so forth., and the extent of analysis that contextualizes these information with validated insights by way of rigorous, multi-center, peer-review research. As additional proof, the American Society of Medical 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 will 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 the planet. It contains tons of of peer-reviewed publications enabled by that information, important 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 are integral to the processes of care and analysis that carry the facility of that information and proof to bear in any respect factors and for all selections alongside a affected person’s care journey. What is absolutely necessary 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 resolution augmentation.
ConcertAI has develop into a number one participant in real-world proof (RWE) and AI expertise for healthcare. What have been among the early challenges you confronted in positioning the corporate as a pacesetter on this house?
It’s a must to be trusted and evolve in the 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 very best pursuits of their sufferers. Belief comes out of your tutorial and trade companions, who see the proof of and consider 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 scientific and scientific follow. You even have to attain a scale that your information options characterize not solely your entire inhabitants but additionally produce conclusions which are confidently generalizable again to the complete inhabitants being handled with a selected drugs. Know-how 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, by way 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 remodeling most cancers analysis and remedy?
I really like that query. We’re engaged on this day by day! The alternatives to supply worth to suppliers, sufferers and innovators are nearly limitless. In early-phase trials, we’re evolving examine simulation approaches with digital twins that may change the applications we take into scientific 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 resolution augmentation AI options will suggest pathways for remedy which are evidence-based and particularly tailor-made to these pathways, monitor responses in keeping with the anticipated response, and search for probably helpful scientific trials when response or profit is under expectations. Our imaging scientific interpretation options function on the stage of operational processes, scientific interpretation, and longer-term view of recent interpretations or new interventions that must be thought of based mostly on insights and proof sooner or later. Not is an motion “as soon as and finished” however fairly it turns into “as soon as, after which many times” 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—this can be a horizontal view versus a collection of slim, deep, vertical views that should 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 Resolution works to match most cancers sufferers with life-saving scientific trials? What influence have you ever seen to this point when it comes to affected person outcomes?
Medical trials are very complicated and require hours of effort by a variety of extremely knowledgeable people. For many organizations, scientific trials are provided as a accountability and dedication to sufferers the place the present normal of care might not characterize a viable different. Trials have not likely been very obtainable 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 accredited medicines. This creates a double dilemma: the vast majority of sufferers who want entry to trials are restricted, and those that are reflective of the final word normal 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 revealed this for the final American Society of Medical Oncology conferences and in different areas. Our strategy is how we expect AI must be applied—as an augmentation of knowledgeable people the place there are giant capability and expertise constraints and the place lives are at stake. We’ve developed a set of orchestrated and tuned giant language fashions that entry affected person information, synthesize traits, and match sufferers to probably helpful trials, doing precisely what the knowledgeable 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 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 strategy to trial design and affected person recruitment tackle among the present limitations in scientific analysis, equivalent to affected person variety and trial effectivity?
I’m pleased with my group—they informed me three to 4 years in the past that reaching variety is an obligation and the correct factor to do scientifically. In addition 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 resolution would combine variety and social determinants of well being traits as our normal strategy. It’s not an choice. It’s simply what we do. Subsequently, our CARAai™ supported scientific 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 are usually not unwittingly excluded, and outline the scientific websites probably to guarantee participation and representativeness. That is the place AI might be “AI for Good” and the place expertise doesn’t introduce a bias however assures that biases don’t enter the method, the final word design, or the operational processes across the scientific trial.
What position does ConcertAI play in lowering the burden on healthcare suppliers and optimizing website choice in scientific trials?
We combine the work burden into all elements of our scientific 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 scientific depth of a examine versus the usual of care, as within the case of extra 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’s additionally a burden on the supplier. If we are able to automate the identification of sufferers for scientific trial eligibility, decrease false positives that create work, and supply what we name “AI leverage” to the work of the Medical Analysis Related, Research Nurses, and Physicians, then the burden is lowered. The identical is true of our AI Automation Resolution, which permits the analysis group to keep away from doing guide information entry—usually 2 to 4 hours on the finish of the day, and sometimes accomplished at house. Early on we seemed 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 develop into 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 at the moment, with a really quick path to over 80% within the coming few months. As these components 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 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 accountability for the American Society of Medical Oncology’s (ASCO) CancerLinQ program. It’s the world’s largest clever well being community, comprising tutorial facilities, regional hospital techniques and group suppliers. A key a part of this community is implementing the ASCO Licensed® high quality and scientific pathway options. Since CancerLinQ is a ConcertAI initiative, now we 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 vital diagnostic exams that might inform remedy selections, and doing the identical for newly accredited medicines that characterize one other or higher remedy different. 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 getting into the sphere is lower than the quantity retiring. Nevertheless, affected person demand is ever-increasing. So, it’s the best space for offering AI SaaS options that help doctor and allied care professionals in each workflow optimization and scientific resolution 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 might be near or similar to knowledgeable 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 information, predictive algorithms for resistance and different components that may all inform the remedy resolution and allow response monitoring. I’ve been within the subject for years and on completely different sides of recent improvements—what we are able to do now’s nicely past something we have been ever in a position to 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 seeking to make a significant influence in healthcare by way of AI?
You may’t be an AI firm with out entry to information at scale. Information is the substrate for constructing coaching and monitoring fashions. Additionally, constructing AI options is a group sport. You want area information at an distinctive depth matched with a brand new technology of AI mannequin improvement capabilities that acknowledges the behaviors of various lessons of AI options and may carry them to bear towards slim aims, particularly tuned for human or above efficiency. Then, these approaches might be orchestrated in numerous methods to characterize a brand new system for working—that’s the place the adjustments happen, and the worth will get delivered. Follow “AI Humility” as every thing is superb and displays issues we couldn’t do even six months earlier than. But, ‘superb’ shouldn’t be essentially a product or a brand new means of working—it’s simply that, expertise doing one thing new. It’s the accountability of the AI firm to make it a brand new means of working and a brand new strategy for delivering an astonishing stage of worth that was by no means accessible earlier than. Lastly, assume it’s worthwhile to show belief in enterprise practices, AI fashions, and resolution transparency. We’re nonetheless early in our societal journey, and we’re those who should earn the belief to carry in regards to the adjustments we’re able to delivering.
Thanks for the good interview, readers who want to be taught extra ought to go to ConcertAI.