Not Just Numbers: Big Data, Artificial Intelligence, Real People

Clinical Researcher—June 2023 (Volume 37, Issue 3)


Edited by Gary W. Cramer (, Managing Editor for ACRP


If you’ve been paying attention, you can likely tell from the themes of many previous installments of this news roundup column that I am a fan of science fiction in all its forms. However, I have to admit that I do not have an especially scientifically oriented mindset. That is to say, in my school days I struggled in settings like chemistry and meteorology classes, I quickly forgot everything I ever learned about advanced math once the tests were over, and I eschewed computer programming to instead take a course in symbolic logic to fulfill the last part of Penn State’s expectations for my quantification credits (and loved it!).

All of this is prelude to my amazement that this issue of Clinical Researcher has somehow come together with a heavy theme of how not to lose track of how real people fit into where the clinical research enterprise is headed with its current deep dive into big data, artificial intelligence, and all the attendant niceties of machine learning, natural language processing, and a whole bunch of other things I don’t really understand. Did I plan it this way? Most certainly not. Am I happy that it happened, anyway? You bet! With so many authors offering me so much material on such topics at the same time, even a Luddite such as myself has to recognize that these things are in the aether, or part of the zeitgeist, or fall under whatever “of the moment” term you wish to use, and I’d be foolish to ignore them. Like I ignore all signs that it’s time to get a new smartphone until the one I’m using experiences catastrophic failure and forces the issue.

Anyway, here are excerpts from various announcements (no endorsements implied) that bolster my feeling that, just like the Continuous Quality Improvements and Just-in-Time Managements of years gone by, I will be unable to avoid editing stuff about these new-fangled tech trends for at least the next decade, so I may as well make my peace with them now.

Some Tech Trends to Keep Track of for the Sake of Research and Development

Scientists in biotech, life sciences, and pharmaceutical research are frequently engaged in a race against time when it comes to surfacing new discoveries and bringing them to market, but their momentum is often hindered by antiquated processes around the collection, documentation, and sharing of data. Information provided by Code Ocean points out that too much of scientists’ and data scientists’ time is spent on low-level data extraction, cleansing, and manipulation tasks. To address this issue, leading innovators in the biotech industry are pursuing a multi-tiered strategy that includes the following activities, among others:

Integrating cloud-based solutions. Cloud solutions offer a smoother, more integrated way to work and minimize collaboration issues between the lab and various stakeholders by providing one place for the data, methods, and software to be shared. According to research from TetraScience, companies are seven times more likely to have to repeat experiments due to data issues that arise when organizations don’t keep their scientific data in the cloud.

Creating standards in analysis workflows. Data operations, data science, and domain science should all use the same data objects, as well as common methods/analyses like gold standards, which are accessible and easy to manage. Establishing analysis workflow standards for all teams enables the data lineage to be traced forward and backward, and allows for the standardization of analysis workflows across the organization.

Enabling self-serve. Up to this point, there has been no such thing as self-serve within models of how research scientists can get at the data collected on their studies while maintaining company-mandated access controls and permission policies. Enabling scientists to have an appropriate level of access to the data, as well as their history, will facilitate better collaboration between study teams and, in the process, immediately accelerate and improve the quality of the results. It will also create more visibility for the work of these scientists within the wider organization.

Transforming Clinical Trial Endpoint Analysis with Artificial Intelligence

Healthcare research technology company Clario has revealed the significant progress it has made in the integration of artificial intelligence (AI) and machine learning into clinical trial data collection through the company’s own development and strategic partnerships. More than 30 solutions have been applied, with more than half of them already active on various Clario platforms. The company says that these integrations have led to an evolution in the way it conducts clinical trial endpoint analyses. “By combining AI tools with deep scientific expertise, [we’re] achieving faster and more accurate results than ever before,” the company noted in a press release in May. “Furthermore, this integration has enhanced operational efficiencies and patient privacy protection.”

“When it comes to AI technology and clinical trials, it’s not about one single solution,” said Todd Rudo, Chief Medical Officer, Clario. “Clinical trials are complicated and unique to the medicine they are researching, so they require bespoke solutions. …We currently have [more than] 70 clinical trials enrolled in our various AI models, and our clients and their patients are already realizing the benefits: enhancements in our ability to collect a wide range of digital data types and subsequently analyze them faster and more accurately.”

“AI is transforming clinical trials, but we have to be thoughtful in how we develop it for such a complex area,” added Achim Schülke, EVP Chief Innovation Officer, Clario. “[Our] approach is to work with our scientific experts to identify meaningful applications of [AI] to improve our performance in data collection and analysis without compromising safety or quality assessments. AI is not a replacement for our scientists, but an effective tool to assist them in their routine work.”

Partnership Leads to Acquisition with Focus on Tackling the “Data Dilemma”

Following an almost two-year partnership between the companies, Digital Science, a technology company serving stakeholders in the research ecosystem, has fully acquired OntoChem GmbH, a company highly specialized in AI-based solutions for finding and extracting key information from internal and external data and text, especially published research. OntoChem will continue to work as part of Digital Science’s portfolio product Dimensions, a linked research database and data infrastructure provider.

Lutz Weber, CEO of OntoChem, said: “More and more, pharmaceutical companies are rapidly advancing their research with the use of AI, machine learning, and other technologies to accelerate their discoveries and to translate those discoveries into real outcomes. One of the biggest issues for pharmaceutical companies is the ‘data dilemma’—there is so much information to sift through that it can be hard to know where to look or how to focus. Even in one field, such as cancer or diabetes, there is a sea of new knowledge being generated each day in very specific areas of research. This is where our work can help to provide that focus, assisting companies with their discovery and decision-making.”

Tech-Driven Solutions to Advance the Patient Experience in Clinical Trials

Veeva Systems and UCB in May announced a collaboration that will focus on technology-driven solutions aimed at improving the patient experience and trial efficiency. The collaboration will see UCB adopt Veeva products for electronic patient-reported outcomes and informed consent to provide a patient-centric, digital experience to study participants and actively influence the strategic direction of these and other applications based on learnings. Together, Veeva and UCB say they aim to set a new industry standard for digital clinical trials with multiple applications that meet the unique needs of patients.

In Other News…

Assentia, Inc., a provider of clinical research services headquartered in Raleigh, N.C., in April announced that it has expanded its global presence by opening an office in Mumbai, India. The formation of this subsidiary and office enables Assentia to establish a hub in the expanding Asia-Pacific clinical trial market, providing support to staff members focusing on global Clinical Trial Agreement negotiation and site payment services in more than 12 countries in the region.