Lessons from the Pandemic: Iterative Data, Iterative Learning
Traditional drug development is excruciatingly slow. From 2010–2020 the average time from the first submission to regulator sign-off was over 9 years, and that’s after potentially decades of R&D to deliver the drug candidate. Yet in response to COVID-19 the pharmaceutical industry, their regulators and governments around the world overcame decades of status quo processes to deliver highly effective vaccines within a single year.
In a society crying out for new infrastructure solutions responding to energy security, climate change and shifting demographics we must learn from this harrowing experience to accelerate the design and delivery of critical infrastructure projects.
Status Quo
Data-fuelled documentation is at the core of pharmaceutical regulation, the design, delivery and results of clinical trials deriving terabytes of insights on the effectiveness or ineffectiveness of prospective drugs and vaccines.
In recent decades the quantity of data captured from each trial has increased exponentially, yet how that data is used, shared and considered had barely changed from the days of hand-typed reports and set square-drawn diagrams.
Typically regulators only received a tiny proportion of the data collected at set milestones, the value hidden behind vacuous report writing. The model increased both costs of clinical trial operations and slowed the decision-making as trials were forced into a stop/start pattern based on the formulation and consideration of documentation.
This may have made sense in a pre-digital world of physical delivery and face-to-face debate but in a Digital-first approach, it was not.
Iterative Data
The pandemic showed the inadequacies of the process, both in terms of the physical limitations of participants being restricted to their own homes and the recognition that such bound processes restricted the pace at which decisions could be made. Vaccine innovators needed to respond far faster than ever before and the regulators recognised new ways of working were needed.
“To do this we implemented rolling data submission to the regulators — we would submit data over time, and be able to amend it over time. This required sophisticated planning in setting up the trial, and designing an operational plan”
Nuala Murphy, Pfizer, Leading Clinical Trials in the UK
Rather than prose-loaded qualitative reports delivered as PDFs, the pharmaceutical teams collaborated with regulators to provide a constant stream of data insights from the trials and accepted back feedback in almost real-time enabling clinical studies to pivot or re-focus where necessary to deliver the outcomes required.
Regulators' culture changed from being passive managers of a process to true collaborators with the teams delivering clinical trials, incentives absolutely aligned to deliver a safe, high-quality vaccine as soon as possible.
Iterative Opportunity
The infrastructure sector could equally learn from this experience, rather than Environmental Impact Assessments (EIAs) delivered on paper by the crate load, an alternative would be to agree on the minimum viable dataset required to provide the assurance needed to proceed. Scheme proposers, industry and regulators would work collaboratively to accept, validate and feedback on data collected in almost real-time, dramatically accelerating decision-making and delivery of critical schemes.
Shifting from qualitative assessment of PDF submissions to quantitative assessment of iteratively improving data would make technical decisions both easier to make and defend from a challenge, driving constructive feedback from proposal stakeholders over adversarial opinion making. When presented effectively, this data-driven approach would enable improved communication between stakeholders, shifting arguments from emotive personal attacks to far more productive challenges on the quality and validity of data collected, hence supporting the delivery team in planning the next iteration of data collection and analysis.
Similarly in the design phase, the industry has often been unwilling to present ‘unfinished’ data and design deliverables, leaving reviews and feedback for pre-scheduled prestige events and milestones often months past the creation of the data or design in question. Taking a more agile and iterative approach, industry and regulators could become far more collaborative, far earlier in the delivery process with feedback provided to delivery teams in days or even hours. BIM, the core technology that enables this has been available off the shelf for more than 20 years, yet many infrastructure projects' approach to regulatory engagement remain not far from the days of drafting tables and set squares.
Across the western world, governments have a new urgency in their requirements to respond to climate change, energy security and shifting demographics. Time has become a luxury that for the most urgent projects is now in short supply. By following a more collaborative, iterative and data-driven approach between scheme proposers, industry and regulators, we would dramatically speed up delivery, improve quality and better manage costs. What are we waiting for?
About Continuum Industries
Continuum Industries is a provider of an AI-powered infrastructure development platform, Optioneer, that enables power, utility and renewables companies to instantly visualise, analyse and comprehensively assess routing options for power lines, cables and pipelines.
By incorporating all environmental constraints into the development process from the very beginning and considering them together with social, engineering and cost criteria, Optioneer bridges the gap between existing routing procedures and the pace at which project development needs to happen to meet Net Zero targets.
