“Tech solutions can bring the trial to the patient, and automation of the data collection/cleaning process. Both would cut down costs of generating clinical trial data considerably – which is the single biggest cost to drug manufacturers.”

Ruby Saharan, Senior Medical Advisor- RWE, Novartis Oncology UK and Ireland

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Clinical trials are incredibly costly and time-consuming endeavors. The average cost to conduct a Phase III trial is estimated at US$20 million, with a median of $41,117 per patient and $3,562 per patient visit. These expenses have reportedly risen by 100% in the last 11 years. With a push to lower the commercial price tags of new drugs – and find ways to get them to market sooner – pharmaceutical companies and regulatory bodies are increasingly more open to new clinical trial methodologies and tools. In parallel, during the current covid-19 pandemic, the pharmaceutical industry is further forced to shift away from traditional clinical trial modalities with a bricks-and-mortar approach – where patients must go to a clinical site for dosing and follow-up – to a more patient-centric approach where the trial comes to the patients in the form of digital enablement. In just a few months, 1,100 clinical trials were disrupted due to lockdown mandates, limited access to clinical sites, and people’s shift in priorities and comfort levels.

It is clear that the $52B clinical trials market needs a makeover. Startups and big tech are actively developing clinical trial solutions, from IoT for remote monitoring to machine learning for electronic health record (EHR) processing to AI-based cybersecurity for data protection. A new report from Research2Guidance (purchase required) discusses the rise in digital decentralized clinical trial (DDCT) technologies since the COVID-19 pandemic. The DDCT solution and service market in Europe and North America (NA) is $1.79 billion (€1.54 billion) and is predicted to grow by 38.5% (CAGR) to reach $9.13 billion (€7.84 billion) by 2026.

“I am impressed by the breadth of service offerings already available from DDCT companies. Solutions are innovating every step of the clinical trial process, from site selection to patient recruitment, and patient onboarding to long term data monitoring.”

Ralf Jahns, Managing Director, Research2Guidance

Now is the time for innovations in clinical trials to provide a patient-centric approach to driving patient engagement and capturing remote and accurate clinical data (including primary endpoints and patient-reported outcomes) and to drive down clinical trial costs. So how might technology innovation impact digital clinical trials? Here are some key areas to consider:

Finding a clinical trial – Matching the proper trial with the right patient is a time-consuming and challenging process for both the clinical study team and the patient. According to research by CB Insights, Roughly 80% of clinical trials fail to meet enrollment timelines, and around one-third of Phase III clinical studies are terminated because of enrollment difficulties. Patients may occasionally get trial recommendations from their doctors if the physician is aware of an ongoing trial. Otherwise, the onus of scouring through ClinicalTrials.gov — a comprehensive federal database of past and ongoing clinical trials — often falls on the patient. Artificial intelligence and machine learning can help extract and analyze relevant information from a patient’s EHR records, compare eligibility criteria for ongoing trials, and recommend matching studies. The challenges in making this work include unstructured data and EHR interoperability.

Challenges with enrollment – Unfortunately, enrollment challenges do not end when a patient chooses a clinical trial. To confirm eligibility, the patient must complete a preliminary phone screen and then undergo examination by a participating site in person or virtually. Every trial includes inclusion and exclusion criteria that each patient must meet to participate. These terms are often riddled with medical jargon that is difficult for patients to decipher. Telehealth services could help streamline this process. If eligible, the patient signs a consent form agreeing to the terms of the clinical trial. This includes awareness of potential side effects, willingness to provide biological samples, and covering expenses not included within the study budget. Solutions using AI to extract information from patient medical records can help simplify the enrollment process by automatically verifying some of the inclusion and exclusion criteria.

Medication adherence – Once patients enroll in a study, they receive the experimental study drug (or placebo). Patients go home with the first course of the medication (for example, a 30-day pill bottle with instructions on dosage) and a diary to fill out daily. Many clinical studies still use paper diaries instead of electronic systems. Patients are asked to note when they took the study drug, what other medications were taken on those days, and any adverse reactions (including headache, stomach ache, or muscle aches). This process is plagued with inefficiencies, including reliance on the patient’s memory, use of paper documents and fax machines to communicate with physicians, risk of dropout. AI and wearables offer real-time, continuous monitoring of physiological and behavioral changes in patients, potentially reducing the cost, frequency, and difficulty of on-site check-ups.

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What about clinical trials for rare diseases? – The FDA classifies more than 6,000 diseases as rare, which means that they affect less than 200,000 people in the United States. Only 5% of these diseases currently have FDA-approved treatments. The first challenge of rare disease trials is the most obvious: it’s hard to find patients. Around 3.5%-6% of people have a disease classified as “rare.” An even smaller percentage will have the specific disease that a clinical trial is attempting to study. Rare disease trials often need to recruit patients from around the world to meet their enrollment goals. But having sites in multiple countries participating means the trial must receive approval from multiple complex regulatory bodies. It also means sponsors must collect and monitor documents and data from many different sites, which involves complex privacy and data regulations and can slow down trials.

One recent example was the decision by the FDA which refused to review Stealth BioTherapeutics’ Barth syndrome drug, telling the company results in a study of just eight patients are insufficient to support its submission. The impasse highlights the challenges of testing drugs for ultra-rare diseases. Barth is so rare that Stealth is unsure it can recruit patients to run a new study

Technology can help rare disease trials increase recruitment rates, improve communication, speed up their workflows, and make the most of the funding they have. Patient recruitment software to identify eligible patients, as well as telemedicine and eConsent to manage remote patient visits, are excellent options for rare disease studies.

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How big tech is supporting digital clinical trials – Big tech companies are leveraging their mobile devices to build platforms that span across the clinical trial process. Since 2015, Apple has been building a clinical study ecosystem around the iPhone and Apple Watch, both of which enable real-time health data collection. Its open-source frameworks — ResearchKit and CareKit — help clinical trials recruit patients and monitor their health remotely.

Google has been more active in the space. The company is building a clinical research ecosystem through its Google Health Studies Android application and developing products through its life science subsidiary, Verily Life Sciences. Verily launched Project Baseline in 2017 to fuel medical research by mapping human health. By mid-2019, Novartis, Sanofi, Otsuka, and Pfizer had partnered with Verily to use its tools for more efficient clinical trials. The initiative has also partnered with Stanford Medicine, the Duke University School of Medicine, and the American Heart Association. In April 2020, Google opened its Cloud Healthcare API to health systems and quickly signed on top medical centers such as Mayo Clinic. These actions follow Google’s 2018 pledge to support healthcare interoperability and data-sharing standards (also signed by Amazon, IBM, Microsoft, and Salesforce). And just this week, Google Care Studio has unveiled a new mobile version of its clinician-facing search tool that helps organize patients’ medical records. The company pitches this new modality as a way for doctors to check in on a patient or access patient information on the go. Currently, Google is in the process of acceptance testing with Ascension and Beth Israel. The company is looking to pilot the tool in Q4 with Ascension. Here’s a short video from Google describing Care Studio:

Another tech company that may enter the space is Facebook, which launched its Preventive Health tool in late 2019. Given the depth of personal data that Facebook captures and its self-organizing communities around health issues, this may be the first step toward a clinical trial recruitment solution.

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What platforms are being developed to support digital clinical trials? – Needless to say, with all of the interest in developing digital clinical trials, there are dozens of companies looking to develop platforms to streamline the workflow across the entire process. The best summary of the current state of the market that I’ve found was reported by Andrea Coravos on her Medium blog. She did a superb job of collecting and summarizing the various market segments, as you can see in the graphic below:

I love her segmentation model, and her most recent article in Health Affairs on how these digital clinical trials will affect patients’ lives is a must-read.

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My take – Today’s potential participants tend to be digital consumers who demand convenience, personalized engagement, and active participation in clinical trials. They want to use digital tools to integrate trial protocols (like medication adherence and care) into their daily lives and not reshape their lives to accommodate the protocols. Each year, more clinical trials incorporate digital tools to monitor patients remotely. Harvard researchers reviewed every trial registered with ClinicalTrials.gov between 2000 and 2017 and found the use of digital tools increased at a 34% compound annual growth rate. Across the study period, the number of registered clinical trials using these devices grew more than tenfold, from eight trials in 2000 to about 1,170 trials in both 2017 and 2018.

Studies have also shown that people are more willing to participate in mobile trials than traditional ones. In a recent survey on patient preferences for using mobile technologies in clinical trials, when given a choice in how to participate in a trial, 81% of respondents reported they were willing to participate in a mobile trial. In comparison, only 51% were willing to participate in a traditional trial.

Many challenges remain, and lessons will be learned as digital research is moved into the mainstream. Still, knowledge of the innumerable benefits to clinical research reinforces the view that now is the time to support digital methods with a focus on learning the most effective and efficient processes.