The reality is, we must figure out ways to shorten pharmaceutical R&D cycle times so that life-saving drugs can reach patients in need more quickly. Technology that supports automated decision-making for efficiently managing unpredictable, complex, and rapidly moving scenarios is part of the answer. An example that we can all relate to is the evolution of transportation and navigation.
In the days of the horse and buggy, travel was slow so people did not travel very far from home. They were typically familiar with the routes and when they did venture to unfamiliar areas, there were not all that many roads to choose from — remaining on course was easy.
As automotive travel increased, more sophisticated navigational decision-making tools were needed. Road maps, despite the near-impossibility of refolding them, were helpful decision-making tools. However, they could not provide directions based on changing factors.
Mapquest, and other mapping tools of the era, were revolutionary. After entering start and end points, possible routes were calculated and the driver printed out turn-by-turn directions. The primary drawback was that these directions could not respond to mid-journey changes - when confronted with changing conditions, or navigational error, their usefulness quickly dissipated.
Finally, we arrive at modern GPS navigation technology that calculates predictive routes based on recent historic and real-time information. These technologies are robust decision-making support tools when course changes are made, as users are notified immediately of navigational errors and provided with suggested course corrections.
HOW TRAVEL NAV APPLIES TO PHARMA R&D
Drug development processes share common steps and stages, and the end goal for every drug is regulatory approval and market success. Like the navigation analogy outlined above, there is a clear start and end point, and many decisions need to be made along the development journey with inevitable course changes.
So how can drug development processes, with changing mid-process steps, be automated? First, we need to understand the differences between flow-centric processes and decision-centric processes.
Flow-centric process designs assume that the order of actions is not variable. A workflow engine determines what happens next based on unchanging rules. Returning to our navigation analogy, a journey that never changes midway in response to traffic, road closures or construction represents a flow-centric process. Flow-centric processes are easy to construct, however, they break down within workflows that do not progress in a serial or completely predictable fashion.
In contrast, decision-centric workflows are driven by the user and constrained by business rules that determine which activities are selectable and/or required. Based on conditions (e.g., the data captured, decisions made, the status of the workflow), the process workflow may present different options. Conditions may change in such a way that some of the planned activities are no longer appropriate, and other activities might become appropriate that were not available before.
Trying to manage a changing process using a flow-centric/procedural workflow involves building complex internal routing, leading to a spider web of possible paths in a workflow diagram. Maintaining this complexity is simply not practical within most organizations.
This is a significant reason why many pharma companies use Excel worksheets and other ad hoc tracking and process design tools. Drug development, and many other processes within life sciences, are most definitely decision-centric. But because most process design software tools cannot handle decision-centric processes without extensive IT development costs and highly trained users, life sciences organizations often piece together process design and tracking tools. However, this ad hoc approach does not facilitate process automation or cross-team collaboration, greatly escalates the risk of errors, adds time and costs.
I have had success using Work-Relay to build/manage complex processes for clients on an enterprise Salesforce platform. Also, we are likely to see more technology tools in the future that tackle decision-centric processes.
