Sina Adibi, CEO, Adaptive Clinical Systems
Sina Adibi, CEOIn recent years, clinical trials have undergone a rapid evolution, accelerated by COVID-19. Distributed clinical trials that require faster clinical data collection are rapidly gaining ground, with advanced medical devices allowing patients to measure and record their health data. This has transformed methods of data capture for clinical studies. With the patients themselves becoming the source of clinical data, clinical study sponsors and contract research organizations (CRO) seek direct access to accurate patient data to speed up clinical trials. However, as the sources for clinical data multiply, inaccuracies and inconsistencies can creep into the captured data. While sponsors and CROs possess intelligent data analytics tools to handle the incoming data, they often lack the ability to combine data from diverse sources, harmonize and normalize it for feeding into analytics tools, and use it in a meaningful manner for the trials.

Making clinical data easily accessible, consistent, and usable for clinical study sponsors and CROs is Adaptive Clinical Systems (ACS). Spinning out from a major CRO, the life sciences technology company integrates clinical data from multiple sources for clinical trials in the pharmaceutical and medical devices sectors. The company’s dedicated team of technologists and software developers has created a platform that connects disparate data sources to solve the lack of interchangeability of clinical trial data among various eClinical systems, electronic medical records (EMR/EHRs), medical devices and digital health technologies. “Our platform is purposebuilt for interoperability with any system used by clinical study sponsors or CROs in a clinical trial,” says Sina Adibi, founder and CEO of Adaptive Clinical Systems.

The “Broker” of Clinical Data

The Adaptive eClinical Bus, ACS’s robust, innovative, cloud-based SaaS platform, acts as an aggregator of clinical data from diverse sources. It seamlessly integrates with the electronic data capture systems (EDC), clinical trial management systems(CTMS), electronic patient-reported outcome (ePRO) and interactive web response systems (IRT), medical imaging, analytics, data acquisition systems, and EHR/EMRs like Epic Systems and Cerner. The Bus features a data view dashboard that contains the whole gamut of information pertaining to clinical data from multiple studies across various levels – from patient to study to the clinical program. Aiding the platform is a range of clinical trial tools – dubbed “connectors” – allowing access to around 90 percent of all available data on eClinical tools, and about 75 percent of EMR records.

Moreover, the platform is equipped with an entire sub-infrastructure for monitoring the clinical data quality.

Adaptive Clinical Systems: Simplifying Data Integration for Clinical Trials

In case it detects noisy or unclear data, the platform traps it and escalates the issue to the source vendors supplying the data, also informing the client. After identifying the root of the anomalous data, ACS applies a patch and revalidates it to adhere to compliance rules. The FDA, HHS, and GCP-compliant platform also has capabilities to accelerate data management and eliminate data transcription errors for trials of all sizes. By leveraging its Adaptive DataVIEW extension, the platform offers CROs and sponsors access to neatly organized, clean clinical data from different sources that provide them a complete, holistic view of their study.

With the platform, ACS oversees the entire clinical trial on behalf of clients, from the initial setup to study launch. At the project initiation stage, ACS builds the data flow architecture for capturing the required clinical data, from which they derive the required configuration needed for the Bus based on the clinical trial protocol and data management plan. Following this, they set up and configure the requisite connectors to pull the clinical data from different sources. Post the setup, ACS lays down the data transformation rules that are used to filter the captured data in accordance with the criteria mentioned in the protocols.

Simultaneously, ACS also takes certain workflow aspects into consideration to filter the data by placing conditionals to determine when and where data is pooled or released. The filtered data is made available to the clients post strict adherence to compliance rules. Here too, ACS takes utmost care to prepare the recorded data documents, executes the data validation process, and also provides clients with the necessary attestations required to authenticate the documents. Finally, once the clinical study commences, ACS constantly monitors the clients’ systems to ensure the proper functioning of the data flows.

Accelerating Clinical Studies with Interoperability

To showcase ACS’s capabilities, Adibi mentions an instance of a client engaged in sourcing clinical data from a large network of hospitals and websites to conduct a clinical study to test a proposed treatment for Type 2 diabetes, as well as to check the feasibility of directly collecting data from EMRs. The client commissioned the company to collect data from all the EMRs in the network and harmonize it. Post normalizing the data and automating the process of data transcription on its platform, ACS uploaded it on an EDC system for the client to perform data management. Data from patient pre-screening for testing eligibility to gathering patient consent, along with data pertaining to clinical care visits and telehealth consultations, enabled the successful conclusion of the yet-to-be-published study with an unmatched degree of precision. “The participants had complete confidence in the accuracy and completeness of the data. It saved them a lot of time, which translates to hard dollars for the CRO and the sponsor,” remarks Adibi.

Our platform is purpose-built for interoperability with any system used by clinical study sponsors or CROs in a clinical trial

Going forward, ACS will be expanding its digital health technologies connector framework in line with the increasing role of patient-operated medical devices used in clinical trials. The company will also remain focused on formalizing its data capture and learning process, which Adibi calls “innovation experience.” To that end, ACS has built a back-office framework where its teams can share and validate their findings and learning experiences with the captured data. Furthermore, the company looks forward to maintaining and managing its portfolio of connectors proactively so that the connectors can be suitably modified in keeping with changes and updates to the healthcare systems. All the while, ACS will be laser-focused on its goal to enhance clinical trial operations with efficient data integration and interoperability capabilities.