Data is the new oil! There is a massive amount of information that is collected by healthcare organizations daily. It includes data from various sources like clinical applications, radiology information, insurance portals, application schedules, lab information systems, and ERPs. To integrate the information flow across all these channels is a very complicated and labor-intensive job. This increases resource consumption, thus reducing efficiency.
To curb these challenges, Robotic Process Automation or RPA in life sciences comes into the picture!
Robotic Process Automation can automate any repetitive task that is critical to the proper functioning of the system. It reduces the workforce utility, reduces the cost, restricts the occurrence of errors, and improve operational efficiency.
Randomized Clinical Trials (RCT) are the golden standards for testing new therapeutics for safety when used in human subjects. Even though the success rates lie between 40-80% across different phases, there is a significant number of failures as well due to patient recruitment. The challenges of conducting RCTs can result in an extended research timeline, which increases the cost of the trials. The factors that impact RCT include the availability of patients, patient retention, availability of principal investigators, trial sites, and study design. The entire RCT lifestyle from research design to its completion is a complex environment ridden with data. RPA would help in optimizing these processes while improving the success rate and efficiency of clinical trials.
Significant development within the pharmaceutical world can be stimulated by quick data integration into complex environments and merging RPA with it to improve and streamline the administrative activities.
Business endpoints that can be optimized using RPA are:
- Patient matching
Establishing a patient population using dynamic inclusion and exclusion to assess the impact of the trial is a tedious task. This process can be automated using RPA. This will help the study designer if any modification is required to enlarge the population of the eligible patients. With RPA execution in the process, the patient matching will be better for the next time. RPA bots can increase the recruitment speed by conducting the initial executions with prospective patients before the final interaction with the clinic associates. It will help in reducing the effort to do redundant tasks during the patient recruitment process for a clinical assessment/study.
- Processing pharma co-vigilance cases
According to ClinicalResearchNewsOnline.com a large pharmaceutical on an average processes 700,000 adverse event cases per year1. With the pressure of these companies to go lean to reduce cost, the concentration is on increasing the caseload while not compromising on the cost base. 50% of the PV resources are used in managing cases that require data integration. As per RoboticsandAutomationNews.com by automating these manual steps, a biopharma company can reduce the time spent on PV by 45%2. Thus, saving multi-million dollars annually.
A major pharma company had automated the reporting from physicians using a messaging robot. The company was adapted to the reporting of adverse drug reaction forms with the help of a pharma bot. The sales representative could easily capture the data from the physicians via mobile phones. This enhanced the real-time reporting, reduction in the compliance risk, and quickly resolved the issues.
Other automation processes are being carried out in the company to ease the paper-based workflow.
- Trial master process management:
The sponsors of a clinical trial record all the activities. It includes multiple sites in a master data repository, which is known as the trial master file (TMF). The document and data are still entered manually in the TMF structures. Sponsors that have multiple CROs have to facilitate multiple TMFs, which are not integrated properly. This limits the insight drawn from a TMF.
On top of that, extra resources must be trained and allotted to maintain and verify each system. RPA would reduce these efforts by automatically uploading the data and documents into the TMF. This could reduce 90% of the time spent on data entry, thus saving millions of dollars per clinical trial a year.
- Regulatory submission process:
The submission process for regulatory activities is a time taking process. This requires the pharma companies to indulge in activities such as tracking the status of documents, and compilation of records. If these tasks are automated with the help of RPA, then it will reduce the time to market considerably.
RPA is the answer to increase the efficiency of redundant but essential administrative tasks in the clinical processes. It is gradually making the pharma firms efficient in focusing on making safe and effective drugs that are available at a lower cost in the market. RPA will help in avoiding delayed drug introduction to the market. It will also help in reassigning higher value tasks to the employees, like core research and development.
Robotic process automation in clinical trials can enhance rule-based workflows and processes. These bots can provide or enhance the storage, data manipulation, system calibration facilities, and transaction processes.
Even though not all pharma companies have implemented RPA, however, the chances of adapting to RPA in the coming decade are exceptionally high. RPA is the obvious solution to automating redundant tasks and following a lean business model to increase profitability. Organizations should judiciously dive into this by analyzing each task and deciding which menial activity needs to be automated. If the activity is chosen is wrong, the firm will not be able to benefit from RPA.
Another critical challenge that RPA must address before its comprehensive execution in the pharma industry is the requirement of proper validation. Since the pharma industry is the enabler of people’s long lives, therefore all the innovations have stringent guidelines by the regulatory authorities for each level. Any system that helps in decision-making requires validation and change control. Any change in the system requires re-validation to precisely provide the desired output or flag the process for further manual interference. In the Pharma industry, RPA cannot manage the validation process, thus often requiring human interference. However, RPA, when configured correctly and made auditable, can address the challenge of validation efficiently.
We have worked with industry leaders in the Life Sciences Industry that include pharmaceutical companies and medical equipment manufacturers to add to their value chain and help them become future-ready with digital transformation.
If you are looking at an RPA solution, speak to us at i2e consulting today!