2023 is a crucial year for clinical research. On one side, we are coming out of a global pandemic. Another side, we are preparing for a wave of future uncertainties. The pandemic has directly changed the clinical trials processes. Patients are now at the centre of clinical trials. Other shifts in the industry are the increasing use of artificial intelligence and big data, preference for participant flexibility, requirements for diversity in trials and Real-World Evidence. Let us have a look on new trends that emerge out of old trends we had earlier.
- Technology Driven Clinical Trial Execution:
| Old Trend | New Trend |
| Data Analysis: Data analysis was traditionally performed using limited statistical methods, which provided narrowed insights into the data. This made it difficult for researchers to identify trends and patterns in the data. | Machine Learning: Machine learning algorithms are being used to analyze large amounts of data generated by clinical trials. These algorithms can identify patterns and predict outcomes more accurately than traditional statistical methods. |
| Patient Recruitment: Patient recruitment was mainly conducted through traditional methods such as referrals, advertisements, and word of mouth – often resulted in a small pool of eligible patients. | Patient Engagement: The use of digital technologies such as mobile apps, wearables, and social media is improving patient engagement in clinical trials. This approach makes it easier to recruit patients. |
- Clinical Trials with Participant Friendly:
| Old Trend | New Trend |
| Location-Based Trials: Clinical trials were mainly conducted at research centers or hospitals, which required participants to be physically present at these locations. This limited the number of participants who could take part in trials. | Remote/Decentralized Trials: The use of digital technologies has enabled remote clinical trials, where participants can take part in trials from the comfort of their homes. This approach has expanded the pool of participants and reduced the burden on research centers. |
| Inflexible Protocols: The protocols for clinical trials were often rigid, leaving little room for participants to customize their experience based on their needs. | Participant-Centered Protocols: Clinical trial protocols are now being designed to be more participant-centered, allowing participants to customize their experience based on their needs which has improved participant engagement and retention in clinical trials. |
- Diversity in Clinical Trials:
| Old Trend | New Trend |
| Homogeneous Populations: Clinical trials were mainly conducted on homogeneous populations, such as white males. This approach led to a lack of representation of other populations in clinical trials. | Diversity Recruitment: Clinical trial sponsors are now actively recruiting diverse populations to ensure that clinical trial populations are more representative of the general population. |
| Language Barriers: Clinical trial materials were often available only in English, making it difficult for non-English speakers to participate in trials. | Language Accessibility: Clinical trial materials are now being made available in multiple languages to improve accessibility for non-English speakers, which increased the participation of non-English speaking populations in clinical trials. |
- Real-world evidence:
| Old Trend | New Trend |
| Limited Data Sources: Real-world evidence studies were mainly conducted using electronic health records or claims data, which were limited in scope. | Multiple Data Sources: Real-world evidence studies are now being conducted using multiple data sources, such as electronic health records, claims data, and patient-generated data, to provide a more comprehensive picture of patient health. |
| Lack of Standardization: There was a lack of standardization in the collection and analysis of real-world evidence data, making it difficult to compare results across studies | Standardization: There is now a focus on standardizing the collection and analysis of real-world evidence data to improve the comparability of results across studies. |
Regulatory bodies, such as the FDA, are increasingly accepting real-world evidence data to support regulatory decisions, such as drug approvals and label expansions.
Conclusion:
The conventional model of conducting trials was laborious and time consuming with very minimum technology adoption. However, in this technology era conducting clinical trials is observed to adopt following models and are more efficient ways with right technology.
- Adaptive Clinical Trials: Adaptive clinical trials are being used to allow for modifications to study design based on interim data, which accelerates the development process and improves patient access to new treatments.
- Patient-Centered Trials: Patient-centered trials are being designed with patient preferences and needs in mind, which increases patient engagement and improves trial outcomes.
- Decentralized Trials: Decentralized trials are being conducted using remote technologies, such as telemedicine and wearable devices, which reduces the burden on patients and improves participation rates.
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