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Data from clinical-grade wearables and AI-powered analytics are enabling the transition from ‘pay-per-pill’ to pay-for-value.
Some estimates now put the cost of developing a new drug at nearly $2.9 billion. Adding to this financial pressure, pharmaceutical companies have little control over what CMS, health plans and PBMs will agree to pay for approved drugs, or if their new drugs will be listed on formularies-often because the value of new drugs is still an unknown.
To overcome some of these challenges, pharma companies are increasingly leveraging digital therapeutics in tandem with pharmacotherapy to optimize the therapy and to efficiently collect real-world evidence of efficacy, outcomes and ROI-as well as data on adherence and quality of life. This approach helps prove value for better reimbursements and formulary inclusion in an emerging value-driven environment.
Digital therapeutics, according to the Digital Therapeutics Alliance, “deliver to patients evidence-based therapeutic interventions that are driven by high-quality software programs to prevent, manage, or treat a medical disorder or disease. They are used independently or in concert with medications, devices, or other therapies to optimize patient care and health outcomes.” Broadly defined, digital therapeutics could include the thousands of health and wellness wearables and apps available to consumers, but the technology that’s leveraged to demonstrate the value of drug therapy and for drug development is far more sophisticated.
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Ideally, data collection occurs via FDA-cleared, clinical-grade wearables that patients wear continuously to capture vital signs and other biometrics. Data from the sensors is integrated with patient-reported data collected via a mobile app. These data are linked with a massive “data lake,” and an FDA-cleared analytics engine identifies trends and provides clinical decision support that signals to providers where adjustments in pharmacotherapy may be needed.
Active and passive data collection and predictive analytics powered by artificial intelligence (AI) and machine learning can offer timely insights into efficacy and outcomes as well as quality of life measures such as functional capacity. When digital therapeutics are leveraged, drug therapy can be titrated for optimal effectiveness-and a worsening condition can be predicted well in advance of when it would have otherwise occurred, enabling earlier interventions.
Here are five ways that digital therapeutics are being leveraged by pharma, managed care, providers and clinical researchers to demonstrate value, to improve R&D, and to ultimately benefit health plan members:
A digital therapeutics platform paired with medication therapy captures data from clinical-grade wearables and uses AI and advanced machine learning to derive dozens of physiology biomarkers. When that data is fed into a data analytics engine, the efficacy-and value-of the medication can be measured.
Digital therapeutics prescribed in tandem with pharmacotherapy can enable payers to reduce costs by leveraging active and passive data collected from patients to optimize medication therapy to achieve guideline-directed targets that improve outcomes. Based on predictive analytics from biometrics captured from wearables and patient-reported data, providers have valuable information about whether a medication may need to be adjusted, and how likely the patient is to be adherent based on symptom improvement and quality of life.
Digital therapeutics also can help providers flag members who are non-adherent to their drug therapy; this approach enables providers to intervene in a timely manner for improved chronic condition management and patient satisfaction. After all, medication only works if the patient actually takes it.
Digital therapeutics platforms-due to their automation and advanced AI, machine-learning and analytical capabilities-offer clinically relevant data to payers and PBMs on outcomes, so the value the medication is delivering can be evaluated and quantified.
This use of digital therapeutics for chronic condition management or any complex medical condition enhances patient engagement by establishing a partnership between provider and patient, in which the data analytics enable the physician to make enhanced care decisions that can decrease costs and improve outcomes. Common conditions where digital therapeutics are adding value include heart failure, pain and oncology. This approach enables providers to optimize drug therapy for optimal efficacy, and to identify symptoms sooner, for earlier interventions that can prevent major medical events. In addition, patient satisfaction is improved, and the patient-physician relationship is strengthened.
The release of the draft guidance is a result of confusion by drug makers who assumed that only the gold standard mortality and hospitalization outcomes would be considered as approval criteria, according to FDA. While this draft guidance was specific to heart failure, FDA pointed out that the type of symptomatic or functional improvement evidence needed to support approval of a heart failure medication does not differ from other chronic conditions and their associated medications.
Digital therapeutics can play a key role in capturing these quality of life measures that are growing in importance, such as functional capacity and patient-reported outcomes. For example, as reported by Managed Healthcare Executive, an FDA grant-funded study is now under way by Yale University School of Medicine-Mayo Clinic Center of Excellence in Regulatory Science and Innovation (Yale-Mayo CERSI) and the digital therapeutics company Biofourmis to measure the correlation between physiology and activity biomarkers in patients with heart failure who were recently released from the hospital. Researchers are pairing such biomarkers with functional capacity and quality-of-life endpoints, such as the six-minute walk test, the Kansas City Cardiomyopathy Questionnaire and lab results.
The study is monitoring patients at home with an FDA-cleared, medical-grade biosensors and the Apple watch. A patient-facing companion app captures physiology data from sensors and questionnaire answers, patient-reported symptoms, guided mobile-based step test results and medication adherence metrics. The data is also being used to assess medication adherence, dose changes and percentage of patients on target dosages of Guideline Directed Heart Failure Therapies.
By leveraging digital therapeutics to focus on patient-centric endpoints, which can be identified much more quickly than hard outcomes such as mortality, this trial could set the stage to speed clinical trial times by at least one to two years-which could not only bring new drugs to market more quickly, but could also decrease drug costs due to lower R&D costs.
Paying for outcomes rather than promises
Digital therapeutics are playing a pivotal role in moving the market from a “pay-per-pill” model to pay-for-value. With the help of this technology, health plans and PBMs can learn in a timely way whether they are paying for outcomes--and not just promises.
Kuldeep Singh Rajput is the founder and CEO of Biofourmis, a fast-growing global digital health company based in Boston, which offers clinically validated software-based therapeutics to provide better outcomes for patients, smarter engagement and tracking tools for clinicians, technology to complement pharmacotherapy and demonstrate its value, and cost-effective solutions for payers.