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Some may find it a bit ironic that the field of life sciences uses so many manual processes to research and operate within the healthcare industry. After all, the human body is full of complex processes that rely on each other to maintain a system balance. Yet, operations within life sciences firms, from clinical development to back-office operations, run in a much less streamlined way that is easily susceptible to human errors.
Implementing digital transformation within life science companies with intelligent automation (IA) can mean a shorter time to market for products. This transformation typically begins with robotic process automation (RPA), a technology connecting employees and digital workers to physical and digital systems to automate manual tasks within a process. As an organization matures, more advanced technologies for data analysis and machine learning (ML) can readily fit into the IA environment, multiplying the benefits of this transformation.
As you read, consider how your current environment supports this transformation. offers many services, including digital workers from SS&C Blue Prism, to accelerate your time-to-value.
Cloud-based rapid automation leads directly to benefits for product discovery as well as business and compliance operations. Let’s look at how this technology vision might be realized in the life sciences industry.
Intelligent automation assists pharmaceutical companies in several key areas, notably:
The process of drug development already applies automation in some individual components, using techniques like in silico drug design, automated synthesis, and high-throughput screening.
These individual components are typically orchestrated by scientists and technicians. By adding a digital workforce to the lab, life sciences organizations can limit manual errors while speeding up drug development from lab to market. More than assistants, digital workers take advantage of large data sets and advanced software to do things a team of scientists might take days to complete.
Intelligent automation allows key drugs to be identified faster. Artificial intelligence (AI) and machine learning (ML) algorithms within the IA environment can analyze data from hundreds or thousands of assays, fed to them with RPA.
From there, the technology can predict the properties of potential drug candidates, streamlining the drug discovery process. Potentially harmful molecules are eliminated from the development process even before being synthesized, leaving more time to focus on realistic candidates.
Preclinical research is optimized as those best structures go through synthesis and testing. Robotics and automated laboratory equipment are already used to perform repetitive tasks like sample preparation and assay execution.
RPA connects these components, reducing cycle time for evaluations by eliminating bottlenecks. In the end, safe drug candidates get to clinical trials faster.
IA dials up the efficiency of clinical trials. Registration and appointment scheduling are transformed to onboard the right participants in record time. All the tests and results in each trial are administered and collected systematically, regardless of where they happen.
Critically, a problem that surfaces in one case gets an instant response and faster protocol changes for all participants. For a process as fragile as a clinical drug trial, any setbacks can have a domino effect, so increased resiliency is incredibly valuable.
These transformations are already making a commercial impact. Pfizer found a novel way to use solutions from SS&C Blue Prism and AWS to process large volumes of clinical trial data, allowing colleagues to process the data ~88% faster with this intelligent automation for support.
As recent global trends show, the market for vaccines and life-saving therapeutics demands both speed and efficacy. Intelligent automation meets consumer expectations for both. By building resilient organizations with IA, you ensure customer needs continue to be met.
A regulated industry such as pharmaceuticals benefits from IA across several spaces:
Regulation plays a critical role in ensuring the safe and effective operation of life sciences companies, but it doesn’t come easily. One enormous benefit of IA is taking routine, mundane tasks off the plates of valuable employees, empowering them to do higher-value work.
Intelligent automation touches many of the business operations in the life sciences, including:
Business operations in life sciences may look different from other industries, but functions like finance and human resources benefit just as much from IA.
This business service configuration with RPA cuts back many of the mundane aspects of operations, allowing professionals to focus more on what makes life science organizations unique. For example, onboarding employees through a regulated industry faster reduces downtime as new staff can start working quickly.
Automation of supply chains opens a tremendous opportunity for cost savings. Supply chain management is connected to systems from operations for research and manufacturing, ensuring that enough materials are available to keep work going.
Further, down the pipeline, predictive analytics allows companies to manufacture the right amount of product to meet demand. Agile supply chains ensure that products are available on retail or pharmacy shelves when they’re needed most. RPA makes vendor management seamless, from validating details during onboarding to processing invoices.
Implementing an RPA-centric operation can even transform customer experiences. Adverse events can be minimized if side effects are predicted by cognitive automation.
That has another benefit as well: fewer customer returns. Medical supplies and drugs serve to improve people’s lives. When they’re available and work as intended, you can expect positive consumer feedback.
The quality control assured by IA throughout earlier healthcare processes leads directly to greater customer satisfaction.
The regulatory environment adds roadblocks and high costs for companies, but it doesn’t need to be this way. A lot of the administrative processes required in a regulated industry can be simplified with RPA. Process mining technology helps staff uncover operations they may not have even thought to automate.
The healthcare field benefits from automating trial compliance. Enhanced data protection, from the secure cloud environment of AWS, ensures compliance with participant information during clinical trials. Plus, people have easy access to complete data sets for filing applications and submitting reports.
Audit readiness is built into all business processes that utilize RPA. The automated processes themselves leave an immutable data trail. IA can aggregate data monitoring so hunting down information never slows down day-to-day business operations.
These and other components of a regulated environment give more public trust in a critical industry. And public trust is good for business.
Well, it sits within a world focused more on improving health than reducing symptoms. It means that everyone who needs access to healthcare can get it and afford it. The ecosystem uses resources efficiently, meaning problems are not compounded.
PWC projects several changes to a transformed life sciences ecosystem, including the use of wearable devices and social media for clinical trial recruitment. While many of these innovations spring up to address completely different use cases, IA allows life sciences to adapt them for revolutionary outcomes.
The great thing about digital transformation is that you can start where you are today; other companies have deployed RPA and similar technologies to do exactly what you want to do. The AWS Marketplace brings these technologies together, making implementation fast and scalable.
If you’d like to dig deeper, check out this eBook to learn about solutions from AWS and SS&C Blue Prism.
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Solutions Guide: SS&C Blue Prism® Intelligent Automation on AWS®
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Guide: Improving Life Sciences with Intelligent Automation
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