Clinical Trials Demand an Ethics-First Approach
Data integrity within pharmaceutical development is an essential aspect of manufacturing safe, effective and high-quality therapies. With the constant pressure to publish studies and pursue approval for new products, intentional and unintentional trial misconduct is a possibility, and it could cause serious ramifications for public health.
Research investigators have a responsibility to maintain quality and report actionable and repeatable results while protecting trial subjects and future patients. While the regulatory framework offers mechanisms to oversee possible deviations, research subjects volunteer to advance a scientific cause in the hope that a therapeutic response will be attained for the studied indication. Even if for that reason alone, it is imperative that investigators be vigilant with regard to the definition, storage, analysis and presentation of data.
Continuous Professional Development
Protecting trial participants and data integrity is no small task - complicated study design, multiple clinical endpoints and global site utilization offer plenty of opportunity for misconduct. However, there are systems that can be implemented to reduce the inherent risk:
Internal and external training: Staying up to date with regulatory guidance and attending regular training seminars or classes has been shown to reduce the risk of unintentional error. Training departments are tasked with clearly outlining an individual's job responsibilities, posting updated good practices (GxP), describing the data responsibility within the employee's role and clearly describing the consequences for any intentional or unintentional violations.
Clear Standard Operating Procedures (SOP): All SOPs need to be easy to digest, simple to reference and consistently re-evaluated. These detailed and written instructions provide a path for appropriate trial conduct that has been approved and verified by leadership, independent review boards and the Food and Drug Administration (FDA). These are instituted not only for training purposes, but for continuous guidance regarding subject data protection, reporting requirements and patient safety.
Without validated, sufficient and high-quality data, clinical trial results would be unusable, wasting valuable time and resources. That's why it's crucial at the start to design a protocol and implement a study that directly matches the study plan. Once attained, the following considerations need to be included:
Internal and external validity: Investigators must first demonstrate that the correct conclusions are drawn from the initial study population. Next, it is the responsibility of the research team to show that the results are generalizable and can be applied to patients outside of the study. Randomization, concealment and blinding have all become the standard practice when designing and carrying out a trial to reduce any bias or random error.
Sufficient data: Sample size planning is vital for the eventual acceptance or rejection of trial data. Hiring an experienced and well-trained biostatistician and epidemiologist will limit random variation, confounding and selection bias when conducting interim analysis, ongoing monitoring and final submission to FDA.
Data Management and Collection
All methods of managing, collecting, storing and reporting data need to be carried out in a precise manner. Submitting meaningful data from observational and randomized controlled clinical trial designs is only as effective as the ability to maintain the integrity of the data. Researchers approach data in a variety of ways including questionnaire surveys, patient reported outcomes, proxy respondents, tested biologic material and electronic health records. Critical practices to follow include:
Updated systems: Pharmaceutical manufacturers must demonstrate qualification and validation when evaluating software to store and analyze trial data. The system must prove that the data-related process is effective and reproducible, while also providing assurances that the data are accurate, complete and reasonable.
Data security: The current era of data confidentiality mandates contemporary data management procedures to ensure data protection and security. While electronic storage and transmission reduces cost and time, it has also led to significant worry about privacy invasion and corruptible data. De-identified data, masked data and limited data sets can help to protect the safety and privacy of subjects, while maintaining data confidentiality. In addition, regularly updated security definitions can limit the risk for system intrusion.
We can never lose sight of the end goal - safe, effective and high-quality products and treatments that improve the quality of life for patients. Operational activities need to be done the right way, every time. Akin to washing your hands before treating a patient, these precautions and best practices need to be second nature and a requirement in all trial operations. Consequently, this will prevent data integrity infractions so we can continue to protect and serve the patient population.
Since the ongoing dialogue pertaining to ethics in research will continue to evolve as access to better technologies and oversight practices is attained, it is our responsibility to match the pace and meet all contemporary issues head-on.
This ultimately boils down to having the appropriate systems in place, a clearly defined vision for success, and the right people supporting the study. In this competitive market, it is even more important to make sure that your services partner has the global network to recruit and retain the best clinical research talent. This enables sponsors to complete studies on time collect the highest quality clinical data by prioritizing strategic planning, quality control, protocol adherence, performance management, process management and program-level visibility.
Actalent is dedicated to this mission as we are committed to continuous personal and professional development, sound epidemiological trial design approaches, and technologically updated data management techniques.
Want to learn more about integrity in research? Contact Actalent now.