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Technological Innovations: Changing Landscape of Clinical Research

Technological Innovations: Changing Landscape of Clinical Research
Nidhi Bajpai - GROUP MANAGER | November 23, 2017
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Co-author: Vibhor Jain

The life sciences industry is under dynamic transition as new technological development and innovations are changing the traditional methods of conducting clinical trials.

Pharmaceutical companies have to tackle lengthy R&D cycles, which contribute to prolonged time to market for the drug, leading to higher costs. They are, therefore, looking at new ways to optimize their current processes and resources.

Patient centricity and data security, with streamlined data flow on a real-time basis, are now at the heart of clinical trials. With regulatory agencies worldwide mandating new guidelines, it becomes critical to the success of the companies to adapt quickly to these standards.

HCL’s Consulting Services and Life Sciences domain expertise along with its industry-specific capabilities and powerful technology portfolio can help organizations in implementation and adoption of the new standards without disturbing the business continuity.

The Future of Clinical Research is Here: Leveraging Technology and Artificial Intelligence to create a remarkable impact

eSource

eSource is the latest buzzword in the clinical research software industry. With the release of FDA guidance document on electronic source (eSource) data in clinical trials, sponsors, and clinical sites are adopting eSource as a data-collecting method in clinical trials. This comprises everything that includes methodology related to direct data capture; for example, using tablets for data collection by integrating them with electronic data sources (like mHealth, medical devices, EHR, EMR, ePRO, eDiaries, Claims, and Rx) and to the current clinical tools (EDC, etc.). This will not only eliminate the need for manual data transcriptions but will also assist to reduce the source data verification (SDV) and editing efforts as data is captured directly from the source. Real-time access to data will help in effective Risk-Based Monitoring (RBM) by application of advanced analytics. With standard and customized algorithmic designs, sponsors can immediately detect risk factors and draw the attention of investigators to any information not in compliance with the protocol.

mHealth

The use of mHealth technologies and wearable devices are bringing about a positive change in the research landscape. As mHealth technologies are becoming more prevalent, they pose a major challenge for the pharmaceutical organizations to upgrade their current systems and procedures.

Clinical trial models based on the integration of wearable devices and smartphones demonstrate compelling benefits, including:

  • The use of wearable devices will assist in real world (RWE), continuous measurement of health status as subjects follow their daily routine
  • Reduced cost by decreasing the need for expensive clinical visits
  • Improvement in subject retention, encouraging compliance, and sharing information which can boost subject participation in research

Artificial Intelligence/Machine Learning

Artificial intelligence (AI) and machine learning are shaping the new normal for the life sciences R&D industry. They present a real opportunity to the industry in assisting clinical researchers in their everyday tasks, such as:

  • Data analysis: Developing meaningful insights by data change (manipulation) and analysis
  • Knowledge sourcing: Knowledge extraction on meaningful clusters from the available scientific publications
  • Drug discovery and manufacturing: Initial screening of drug compounds to predict success rate
  • Deriving business intelligence: Enabling researchers make therapeutic decisions to predict clinical outcomes

The following are the few applications:

The principles of advance analytics have played an immense role in achieving target patient enrollment for the trials. However, if they are supported by AI, the arena gets wider — thus, increasing the possibility of subject identification and retention by many folds.

AI-enabled platforms in conjugation with mHealth devices can help investigators track inconsistencies in patterns of medicine intake among patients on a real-time basis, thereby ensuring strict adherence to the dose regimen by remote monitoring. It can also optimize the process by detecting future trends and negative signals ahead of time.

AI can help life science companies predict the effectiveness of a medication for a particular condition by deploying computerized reasoning for forecasting drug results (safety/efficacy) based on current/historical data; for example, to predict (based on human gene data) how different people will react differently to the same medication. With the use of AI, it will be possible for companies to project which subjects with a particular disease condition would gain the most from the drug. Machine learning also helps to ensure drug safety by helping in timely detection of biological and other signals for any sign of harm to participants.

Next Generation Clinical Platform by HCL

The continuous technological advancements provide abundant prospects for the organizations to improve all aspects of the clinical trial methodology. The Next Generation Clinical Platform (NGCP) by HCL for clinical research has been developed with an aim to support companies in transforming their current clinical trial processes and practices.

The NGCP with its Artificial Intelligence and Machine Learning capabilities supported by eSource (mHealth/IoT) and Analytics will help improve research performance by foreseeing the future out-comes and averting risks.

The elementary data workflow for the trial process is as follows:

Elementary

The NGCP will empower teams to view trial data in real time, helping them optimize the way they work while letting them take proactive measures to improve the decision-making. The NGCP, along with HCL’s Strategic Consulting Capabilities, facilitate a centralized access to clinical trial information. It aids the sponsors to collaborate more effectively with the sites, CROs, and regulators for error-free sharing of trial-related information on a real-time basis.

There is a need for companies to define a clear strategy to take the benefit of these technological advancements with a clear focus on patient centricity and improving the overall trial experience for all the parties involved.

HCL is continuously working with key clients, partners and industry leading stakeholders to develop new and innovative solutions for Life Sciences industry. Our Business consultant teams work closely with the leading Life Sciences companies to assist them in enhancing and transforming their clinical trial processes in a cost effective and efficient manner by optimizing their current resources.


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