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 scientific research utilizing supplier EMRs, LISs, and PACSs methods because the supply for all research information. It’s a long-term companion companion 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 companion 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 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 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 enables inferencing and prediction. This included predicting occasions to keep away from, comparable to sufferers’ non-adherence to their remedy or discontinuation of care due to an absence of constructive response, which knowledgeable when scientific trials is perhaps the following 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 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 complete market’s improvements—the journey to this point has been terribly productive and exhilarating.
Now we have 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 using digital twins as a decision-enhancing instrument for care and analysis.
Immediately, we serve nearly 50 biopharma innovators and a pair of,000 healthcare suppliers—so whereas not at fairly the dimensions of your complete market, we’re the broadest-reaching AI options for oncology within the business.
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 “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 completely new technology of analysis and seed funding funding for educational, neighborhood, 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 information, and many others., and the extent of analysis that contextualizes these information with validated insights via 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’ll 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 consists of a whole lot of peer-reviewed publications enabled by that information, important proof ensuing from these publications altering how sufferers are handled and assuring essentially the most constructive potential outcomes, and now AI SaaS applied sciences which can be integral to the processes of care and analysis that convey 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 actually vital right here is that we don’t do that unilaterally. It’s accomplished 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 change into a number one participant in real-world proof (RWE) and AI expertise for healthcare. What have been a few of the early challenges you confronted in positioning the corporate as a frontrunner 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 perfect pursuits of their sufferers. Belief comes out of your tutorial and business 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 observe. You even have to attain a scale that your information options characterize not solely your complete inhabitants but additionally produce conclusions which can be confidently generalizable again to the complete inhabitants being handled with a specific drugs. Expertise is comparable. Scientists and clinicians are inherently skeptical—as they need to be—and don’t belief black containers or algorithms they don’t perceive. So we would have liked to determine 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 information create for remodeling most cancers analysis and remedy?
I like that query. We’re engaged on this day-after-day! The alternatives to supply 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 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%—which means new medicines get to sufferers quicker. Our choice augmentation AI options will advocate pathways for remedy which can be evidence-based and particularly tailor-made to these pathways, monitor responses according to the expected response, and search for doubtlessly useful 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 latest interpretations or new interventions that must be thought of primarily based on insights and proof sooner or later. Not is an motion “as soon as and accomplished” however quite it turns into “as soon as, after which many times” 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—it is a horizontal view versus a collection of slender, 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 skilled 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 advanced and require hours of effort by a variety of extremely skilled people. For many organizations, scientific trials are supplied as a duty and dedication to sufferers the place the present commonplace of care might not characterize a viable different. Trials have not likely been very accessible to sufferers in neighborhood 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 people who are reflective of the last word commonplace 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 printed this for the final American Society of Medical Oncology conferences and in different areas. Our method is how we expect AI must be applied—as an augmentation of skilled people the place there are giant capability and expertise constraints and the place lives are at stake. Now we have 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 totally documented method to creating suggestions and assessments. Within the websites the place our applied sciences are deployed, we carry out on the stage of essentially 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 deal with a few of the present limitations in scientific analysis, comparable to affected person variety and trial effectivity?
I’m pleased with my group—they instructed me three to 4 years in the past that attaining variety is an obligation and the appropriate factor to do scientifically. Additionally they maintained that it’s onerous 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 commonplace method. It’s not an possibility. 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, make sure that these populations aren’t unwittingly excluded, and outline the scientific websites most probably to guarantee participation and representativeness. That is the place AI will 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 scientific trial.
What position does ConcertAI play in decreasing the burden on healthcare suppliers and optimizing web site choice in scientific trials?
We combine the work burden into all points of our scientific trial options. First, there’s a burden on the affected person. This may be the place the location is positioned, the variety of visits required for a research versus the usual of care, or the scientific 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 scientific trial eligibility, reduce 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—sometimes 2 to 4 hours on the finish of the day, and infrequently accomplished at dwelling. 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 change 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 in the present day, with a really quick path to over 80% within the coming few months. As these parts come collectively, we’ll get the workers 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 customized most cancers remedies?
We’ve not mentioned this an excessive amount of since final yr. In December 2023, we assumed duty 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 methods and neighborhood 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, we’ve got 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 assessments 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 accomplished 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 yr’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 ideally suited space for offering AI SaaS options that assist doctor and allied care professionals in each workflow optimization and scientific 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 outstanding. Non-inferiority research mirror that AI fashions will be near or akin to skilled people in slender 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 information, predictive algorithms for resistance and different parts that can all inform the remedy choice and allow response monitoring. I’ve been within the discipline for years and on totally different sides of latest 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 wonderful.
As an skilled chief in healthcare expertise, what recommendation would you provide to new firms trying to make a significant influence in healthcare via AI?
You possibly can’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 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 convey them to bear towards slender targets, particularly tuned for human or above efficiency. Then, these approaches will 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. Apply “AI Humility” as every part is wonderful and displays issues we couldn’t do even six months earlier than. But, ‘wonderful’ is just not essentially a product or a brand new means 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 means of working and a brand new method for delivering an astonishing stage of worth that was by no means accessible earlier than. Lastly, assume it’s good to exhibit belief in enterprise practices, AI fashions, and resolution transparency. We’re nonetheless early in our societal journey, and we’re those who need to earn the belief to convey 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.
