Essential to the future of cancer immunotherapies is a digital health infrastructure that can support reliable, secure and compliant data collection from disparate systems and devices. As more and more immuno-oncology (IO) treatments come to market, biopharma will require data to enable more efficient research and development; providers will require data to drive more personalized treatments and payers will require data that enables them to make informed decisions about which therapies to cover.
There are new data-related challenges as well. Far more data are becoming available to oncologists, caregivers, insurers, biopharma companies, and other stakeholders, making it more difficult to parse the data that are actionable and valuable. IO combination therapies are gaining approval for the treatment of a wide variety of conditions.
A new whitepaper from BrightInsight highlights how digital health can meet these challenges head on. Leveraging data more efficiently can enable more targeted interventions, improve outcomes by enabling precision medicine and better patient matching, and expand patient access by easing clinical trial enrollment and reimbursement. In an interview, BrightInsight Co-founder and CEO Kal Patel, MD offered a preview of the report, The Role of Digital Health in Immuno-oncology Therapy Development and Adoption.
The rise of remote patient monitoring tools is widening the patient recruitment pool for clinical trials because they reduce the need for patients to be located near Academic Medical Centers. They also have the potential to reduce healthcare disparities by creating a more diverse patient population for these clinical trials. The growing sophistication of these devices means they not only can track biometrics but also spot adverse events with immunotherapies, such as fevers associated with a “Cytokine storm”, the body’s inflammatory response to certain immunotherapies which can also reveal their positive effect.
“On the one hand you have this amazing period of innovation that’s happened with immuno-oncology solutions,” said Patel. “But because of the data challenges, there’s a mismatch between all this rapid innovation with tremendous promise, and very small patient pools…We need to bring that matching capability through from R&D to the Commercial side.”
An astonishing fact of clinical trials in oncology is that, as expensive and time-consuming as the recruitment process is, only 8.1 percent of oncology patients participate in clinical trials. That’s due, in part, to the burdensome task of identifying a clinical trial at another institution or geographic area. If ever there were a problem in search of a digital solution, it’s this, but it’s still only one part of a complex issue.
Precision medicine is poised to make this need even greater. Companies developing oncology therapies that are designed to target tumors with specific traits require a sophisticated chain of data to connect the biopharma companies with oncologists and their patients. That requires the development of companion diagnostics in tandem to properly screen for these therapies. For example, current patient matching protocol is based on PDL-1 levels. PDL-1 is a protein that plays a vital role in preventing immune cells from attacking non-harmful cells in the body. Some cancer cells have a large amount of PDL-1. The problem is that measuring PDL-1 in a cancer patient’s tumor is only a snapshot in time that can easily change if the patient is receiving chemotherapy. It calls for a more robust patient matching system—matching therapy testing to the patient population with the right benchmark to compare it against.
Teri Foy, Bristol Myers Squibb Senior Vice President of Immuno-oncology and Cellular Therapy, speculates in the report that digital could have a transformative effect in improving patient matching and treatment protocols.
“If we could crack that, response rates would increase because you’d be selecting those patients, based on the features of their tumor and their immune response, who are more likely to have a good outcome. Using digital technologies, you could even help interrogate that data over time, incorporating different markers, or use the data in a different way that would be hugely helpful.”
AstraZeneca offers an interesting case in point. The pharma company developed a vaccine for Covid-19 that requires a half dose to be taken before a full dose injection several days later. It was an accident, apparently, but it ended up being more effective than what was called for in the original protocol.
Patel views AstraZeneca’s happy accident as the kind of revelation that insights from big data collected in clinical trials of cancer immunotherapies could trigger. They can also lead to the development of clinical decision support tools classified as Software as a Medical Device that can advise clinicians on appropriate dosage levels for each patient.
“In the real world, you’re collecting this robust data and you’ve got a common infrastructure so you can pull larger and larger data sets, which unlocks a whole world of insights. It will help match the right patients to the right drug, minimize side effects, and predict recurrence,” Patel said.
Payers will only reimburse a finite number of oncology therapeutics. So, it’s imperative for pharma companies to collect many types of data from clinical trials to give a full picture of each therapeutic. Also of interest to payers will be whether these therapies can reduce or eliminate the amount of time patients spend as inpatients or outpatients. Not only should the data quantify the treatment’s effectiveness and safety, but also include factors such as detailed side effects that impact patients’ quality of life.
Informatics and predictive sciences can help bring all that information together, whether it is around cell therapies, drug product characteristics or translational data being sampled during the trials. Digital tools can improve matching patients to therapies and predicting adverse reaction, with the growing use of AI- and machine learning-based algorithms predicting who will respond to treatment or not.
While not validated as complementary or companion diagnostics, wearables do provide valuable insights into patient responses. Obtaining more biometric markers in the composite score would offer valuable support. Taking data points and pulling them together can define either correlations in responses or predictors of other patients that will respond.
Joachim Reischl, Vice President, Head of Diagnostic Sciences, AstraZeneca, comments in the report, “we need to think about the patient journey. We should work toward treatment tools that capture the patient journey more holistically and go beyond a specific treatment modality. This may help to reduce the current fragmentation and improve the patient journey.”
“I think it’s really an obligation of the industry to take a digital-first approach. As we know today, the biopharma sector is still using too much paper. When you are talking about patient-reported outcomes, there’s a huge opportunity to digitize,” Patel notes.
To request access to BrightInsight’s white paper on The Role of Digital Health in Immuno-Oncology Therapy Development and Adoption, click here.
Photo: metamorworks, Getty Images
