You can’t spell pharmaceutical without R, P and A

Companies today are taking longer than ever to bring new drugs to the market as factors such as complex protocol design and recruitment delays continue to drive up the cycle time. Ian Pollard, SVP Sales, EMEA North and South, at Signavio, offers a solution

Looking at the top companies in the pharmaceutical industry, Deloitte found that R&D returns have steadily declined since 2010 — down to 1.8% in 2019.1 At the same time, the average forecast peak sales per pipeline asset fell below $400 million for the first time ever — to $376 million — in 2019.

The cost of bringing a new drug to market remains close to two billion dollars, as clinical trial cycle times continue to move past the standards set even 5 years ago.

When bringing a new product to market, researching the regulations and understanding the product registration process can take months, if not years. Maintaining compliance with an ever-shifting regulatory framework adds even more time and money to the process.

Of course, the costs of non-compliance are even greater: as PharmaiQ as noted, a simple warning letter from the US Food and Drug Administration can cost hundreds of thousands of dollars.2 Just to take one example, in 2019, drug manufacturer Akorn received a warning letter and watched company shares immediately drop 12% the following day.

Faced with these kinds of sobering statistics, pharmaceutical organisations are on the hunt for any and all technologies or operational changes that can help to bring the cost of R&D back down to Earth. For many, this has meant aiming to speed up R&D tasks such as patient selection and enrolment, protocol design and support site selection, as well as more efficiently record patient-reported outcomes and other results.

To do so, many pharmaceutical companies have embarked on quick-fix robotic process automation (RPA) programmes.

Avoiding the rush to automate

Companies often approach these RPA initiatives expecting to realise significant benefits — saving time and money, reducing rework, improving accuracy and freeing up employees to focus on growing the business — quickly, with minimal effort and little or no disruption to current processes or applications. However, most soon understand that implementing RPA is more challenging than they had anticipated.

This optimism and resulting disappointment is reflected in industry research. A recent PwC survey found that organisations consistently (and significantly) underestimate the requirements of implementing RPA, with proof of concept projects almost always taking longer than expected to complete.3

Even when organisations do complete their pilot projects successfully, they face challenges when rolling out the RPA programme to the entire enterprise. Clearly, one of the first obstacles to effective RPA implementation is the understandable desire to get started with RPA as soon as possible!

What is missed in this drive to automation is why certain processes are more suited to RPA than others. Although the market for RPA tools is maturing rapidly, the current capabilities of RPA tools make them most suitable for tasks that are repetitive and methodical, whereby decisions are rules-based and can be explicitly specified.

Tasks or decisions that need human experience and expertise (such as the intuitive leaps often called for in the development of a new pharmaceutical product) cannot be automated using current RPA tools.

Those tasks that are suitable for automation share a common set of characteristics, however, which are included in the list below.

Repetitive and routine: Bots work by repeating a certain sequence much faster and more efficiently than a human ever could. This is made significantly more difficult and likely beyond a bot’s capability, if the tasks making up a process need to be individually assessed for variations.

Susceptible to human error: Humans struggle to maintain complete accuracy when undertaking repetitive, mundane, detail-oriented tasks. Bots don’t get tired or distracted, removing or reducing the possibility of human error.

Based on specific rules: Any RPA system or piece of software responds only to the instructions it is given, meaning it will need a clear “if/then” structure to operate effectively.

Focused on digital data: RPA is a software solution, meaning the data it is working with must be available in a digital format.

High volume and high priority: If a process is only undertaken rarely, or there is no particular deadline or time pressure, it will be difficult to take advantage of RPA’s ability to handle a large volume of information very quickly.

However, even once they have identified the right kinds of processes to automate, many organisations are then confronted by the fact that the processes to be automated are not documented, standardised or optimised. In other words, the underlying quality of the processes being automated is not sufficient to gain the expected benefits.

Building the foundation for RPA

With the goal of rapid implementation taking precedence, suboptimal processes can often be automated without any consideration regarding how those processes actually play out in the real world.

Depending on the RPA tool being used, decision logic within the processes that may have been built up organically for years is also targeted for automation without challenging whether that logic continues to apply in the current reality. With this approach, organisations end up automating bad processes and decisions … with predictably poor results.

The necessity of optimising processes before automating them makes effective business process management (BPM) a prerequisite to a successful RPA solution. Both RPA and BPM emphasise the importance of planning and consistency when implementing large-scale change within an organisation … and when seeking to improve the ways in which that organisation does its work.

In addition, leveraging new and upcoming technology to rethink the design of a process has been a fundamental component of effective BPM for almost 30 years now, meaning organisations that embrace a process-oriented culture are well-placed to reap the greatest reward from their RPA implementation.

RPA helps organisations to work more quickly, whereas BPM ensures decision making keeps up with this increased pace by helping employees to make better decisions faster.

RPA is potentially one of the biggest drivers of business transformation and getting people on the same page about where and how RPA can make a difference is half the challenge.

BPM supports business transformation by increasing process transparency and visibility, encouraging knowledge sharing, collaboration and engagement, and acts as a solid foundation for the standardisation of activities across an entire organisation.

With a focus on highly efficient, quality centric processes and a supply chain that must be scalable and agile enough to accommodate changing scenarios and partners across the globe, the usually large businesses that make up the pharmaceutical industry have a strong incentive to define and unify business processes, break down barriers between organisational and geographic divisions, and improve global collaboration and innovation.

BPM, RPA and the pharmaceutical industry

For the pharmaceutical industry, BPM can offer a flexible framework that can be individually tailored to each organisation’s needs, either as an end in itself or as a precursor to effective automation. Even a small sample of possible applications could include

  • tracking clinical investigators, including the number of patients seen and whether patient reports meet industry standards and research protocol
  • the process for developing medication labelling documents, which involves collaboration across many stakeholders and approvals that have to be obtained from regulators worldwide
  • modernising IT infrastructure without adding significant capital expenditure, through hosted workspaces, meaning pharmaceutical companies can work to customise and implement a secure and effective cloud-based enterprise quality management (EQM) strategy
  • clearing employee “choke points” where information is collected or recorded manually; in these cases, as well as automating the collection, RPA in conjunction with BPM can provide email notifications and reminders to prompt workers to perform tasks and keep things moving.

In addition to these points, regulatory compliance is a focus area all of its own. A reliance on complex, manual or paper-based compliance systems can prevent pharmaceutical companies from becoming sufficiently agile and responsive; furthermore, siloed functional units and lines of business can lead to a lack of accountability, as well as an inability to comprehend the full risk profile of a particular process.

A compliance framework based on BPM and supported by RPA means compliance considerations can be built into the structure of a company’s processes. Even the time taken to actually prepare regulatory submissions, from data collection to tracking documents and preparing dossiers, can be dramatically reduced using RPA.

In effect, compliance itself becomes automated, a major benefit when dealing with the complex regulatory environment within which pharmaceutical companies operate.

Conclusion

Currently, RPA is largely considered to be an “add-on” that attaches to existing systems and processes to improve their efficiency. This is a tactical solution, which decreases costs and increases speed in a relatively short time and can be an effective mechanism for pharmaceutical companies looking for “quick wins.”

However, in the rush to automation, there is a tendency to forget the “P” in RPA: process. A more detailed, enterprise-level focus can lead to lasting positive changes that reduce R&D cycle times, cut down on costs for the long-term and enhance compliance frameworks.

Although RPA tools provide exciting new possibilities to improve process performance, to effectively realise these possibilities, RPA tools should be used in the context of existing process improvement methodologies. In other words, when pharmaceutical companies are thinking about RPA, as with any other aspect of optimising a business, process is paramount.

References

  1. www2.deloitte.com/us/en/pages/life-sciences-and-health-care/articles/measuring-return-from-pharmaceutical-innovation.html?id=us:2em:3cc:4dcom_share:5awa:6dcom:life_sciences_and_healthcare.
  2. www.pharma-iq.com/regulatorylegal/articles/the-growing-need-for-regtech-in-the-pharmaceutical-industry#:~:text=According%20to%20a%20research%20report,regulatory%20requirements%20are%20not%20met.
  3. www.pwc.dk/da/publikationer/2017/rpa-danish-market-survey-2017-uk-pwc.pdf.
  4. Companies