Recently Inteliquet’s David Hadley, PhD, our Director of Data Science, was recognized as a member of the 2020 class of “40 Under 40 in Cancer.”
David’s extensive experience in clinical research and clinical decision support has made him well-adept at parsing out clinical data and leveraging it to provide meaningful contexts that provide insights and findings that can improve clinical practice.
Why Did We Nominate David?
Since 1999, David’s passion emerged at the intersection of human-computer interaction and databases. He focused on the management and epidemiological analysis of large datasets. He worked in the beginnings of precision medicine, which allows doctors to select treatments based on a genetic understanding of the patient’s disease, and to create personalized treatment plans.
With a PhD in epidemiology, and a particular focus on genetic epidemiology, his extensive experience in clinical research and clinical decision support has made him well-adept at parsing out clinical data and leveraging it to provide meaningful contexts that provide insights and findings that can improve clinical practice. He also has experience in both quantitative trait and case-control analyses in genome-wide association studies, an important element to precision medicine and a precursor to his work at Inteliquet.
Since joining Inteliquet in 2014, David has focused on complex statistical and epidemiological analyses of client hospital datasets of oncology and pediatric intensive care cohorts with the goal of creating prototypes of clinical decision support tools.
Finding New Oncology “Patient Haystacks”
One area of focus includes improving the process of recruiting patients for clinical trials, especially complex oncology trials, powered by real-world data. This work involves identifying proper clinical data from hospital databases and electronic medical records to improve the process of finding and recruiting patients for oncology clinical trials, currently a labor-intensive process. He helps develop methods to automate these tedious manual search processes that benefit patients as well as their physicians. These include methods of patient volume forecasting, clinical trial digitization, and machine learning that enhances clinical trial design based on real-world patient histories.
“David has a unique ability to look at datasets and see potential that others may have missed or not previously considered,” said one colleague. “For one pharma client’s oncology trial, David found and modeled a method that would allow the client to broaden eligibility and access a new pool of patients. Put another way, he has an excellent ability to find ‘new haystacks’ in which to look for patients that hadn’t been considered previously, which clients appreciated. He has a gift for finding novel approaches and taking the work to the next level to benefit a trial and additional patients.”
Work in Pediatrics: Allowing PICU Physicians To Assess Patients At Risk
Another area of his work involves pioneering bioinformatics research and clinical decision support projects to support physicians in real time. One example includes a 2015 project where the Inteliquet team developed clinical decision support systems for a well-known children’s hospital in the Midwest. The project involved finding methods to better assess mortality risk in a pediatric intensive care unit (PICU).
The physician in charge wanted to use published mortality-risk-factor data in pediatric populations to evaluate patient vitals in real time, so PICU clinicians could better assess patients at high risk and the factors that were increasing that risk [e.g., respiratory rates and oxygen saturation (SaO2) levels]. According to the physician, David’s approach to the work stood out. “First of all, we didn’t have any automated AI or Machine Learning tools at this time, but David was effective at going into ‘messy data sets’ and bringing them together coherently.”
The physician also notes the mindset that David brought to this work. “He operates and collaborates effectively with clinicians, engineers, and analysts because he is open to what others bring to the table to inform his own piece of the puzzle,” he said. “David consistently saw challenges from a clinician’s point of view, which is vital in developing such complex software. His flexibility, imagination, and initiative allowed us to understand the enormous potential of using EMR data to find patterns and create insights that can help us in clinical decision making at these patients’ bedsides.”
Contributions to Areas of Real-world Data
David has made significant contributions in the area of real-world data.
- At the 2019 American Society of Clinical Oncology (ASCO) Annual Meeting, he presented an abstract discussing a new approach to support community oncology practices in building clinical research programs. His work demonstrated an exemplary combination of cancer diagnosis with a single laboratory test and found patients who could be considered for trials though were deemed ineligible due to a narrowly missed requirement. Many such tests vary over time (e.g., by cancer type, prior treatment, comorbidities) and should be considered in the context of other test results. By using real-world evidence at the time of trial design, clinical trials can be optimized to allow improved patient recruitment and expanded availability to patients while ensuring clinical suitability. The idea is to work on re-thinking clinical trial criteria to make them less boilerplate and more tailored towards patients that oncologists are trying to treat.
- At the 2020 ASCO Annual Meeting, David presented an abstract, in collaboration with Honor Health, to look for patterns in pancreatic cancer patients with brain metastases to help find at-risk patients earlier in their treatment. The exploratory data used is the largest dataset of patients with the condition published to date.
For his dedication to promoting data clarity, providing great insight, and dedicating his work to improving patient outcomes, we are pleased to recognize David Hadley, PhD, and his selection as a “40 Under 40 In Cancer Rising Star and Emerging Leader.”
Find more information about the awards initiative here.