Mounting competition in drug development is fuelling a need for speed. From big pharma to emerging biotech – expediting R&D timelines is mission critical to reach approval and commercialisation milestones faster, deliver new innovations to patients and maximise profit margins.
Resultingly, the industry is embracing artificial intelligence (AI) at a rate of knots, harnessing it across the entire value chain to optimise processes and deliver against increasingly ambitious KPIs.
Yet without the right people, with the right tools at their disposal to empower the formulation of novel ideas that can be developed into winning commercialisation plans, AI’s potential is hampered.
Before AI can deliver value, winning strategies must be developed and deployed. And people are key in achieving this. However, with disparate teams, it’s easy to slip into a silo mentality and fall at the first hurdle. To avoid this, teams must be empowered to move as one to make timely decisions and develop confident, powerful strategies that ensure innovations are delivered successfully and to a receptive market.
Approach with caution
AI-powered tools can analyse vast datasets to identify potential drug candidates, predict product efficacy and personalise treatments, all leading to more efficient and effective R&D. Machine learning can also help in designing efficient preclinical and clinical trials, via scenario simulation and by predicting how different compounds will interact with biological targets. This can lead to more targeted and cost-effective operations.
But AI isn’t a silver bullet for BioPharmas and here’s why:
- Without appropriate due diligence, AI can cause more harm than help; creating significant issues for already resource-stretched BioPharmas.
- AI can often take longer to implement than anticipated, due to unforeseen restrictions elsewhere in the organisation.
- A lack of guidelines, along with rigorous validation requirements and regulator scepticism concerning AI algorithms, can derail approvals processes.
- AI typically requires a sizeable investment to ensure the right infrastructure, talent and training to maximise impact.
- AI can have a negative workforce impact; not only is there a shortage of professionals with expertise across AI, biology and pharmacology but automation can equal job displacement and create resistance.
With the end game being to ensure patient safety, these pitfalls need to be managed carefully for AI to be successfully adopted.
People first
For innovation to flourish then, we need to recognise AI as a collaborative partner, not a decision maker. AI can stimulate creativity and augment human judgement, but it lacks contextual and ethical reasoning. With this shift in perspective, we acknowledge that it is people who can make the biggest difference.
But how can people working across functions, geographies and time zones come together to make timely decisions and develop confident, powerful strategies that ensure innovations are delivered quickly, successfully, and to a receptive market?
This starts with addressing the disparate nature of BioPharma teams and empowering people to effectively communicate and coordinate innovations, harness bright ideas and share insights and experiences with colleagues.
The drive to digitise drug development, through AI or other tools, is evident but the starting point should always be people. Bringing them together to cocreate as part of the innovation process and enabling participation from myriad talent pools will secure diverse insights, spark new thinking and smarter decisions.
Collaborative strategy development
Making this concept a reality requires collaborative strategy platforms where teams can meet, engage, share and cocreate.
Nmblr’s collaborative strategy platform, developed to partner with BioPharma teams, facilitates this objective; providing a dynamic, collaborative space that supports people to align on decisions that help shape the product and market appropriately.
By giving people a platform to cocreate, BioPharmas can:
- Harness cross-functional partnerships to collate and transfer knowledge and devise and implement clearer strategies.
- Reduce reliance on disjointed systems that contribute to siloed working practices, conflicting goals and missed opportunities.
- Innovate and make crucial high-stakes decisions at the most opportune time.
- Address commercial challenges to efficiently progress products to market.
- Guide teams through complex choices with ease.
With poor strategic direction cited by many industry leaders as a key reason why their business strategies fall short, rolling out AI systems is akin to papering over the cracks. What’s needed is a focus on bringing talented people together and making it easy for them to collaboratively develop life-changing ideas and define a clear route to commercial success. With these strong foundations in place, unified, winning strategies that enhance patient access, experience and outcomes will follow.