In October 2024, I attended and moderated a panel session at the New Product Planning (NPP) Summit in Boston. The NPP Summit is a gathering of biopharma and pharma professionals focusing on commercial and other NPP topics with lots of insightful presentations, networking, small group discussions, case studies and learning from others.

Here are my 5 key takeaways from the event:

1. You can’t afford to make any mistakes but if so, fail early

There is always a statement from a speaker that seems to stick in the mind even long after the event. Against the backdrop of another year of lacklustre investment in the biopharma industry and IRA forcing many companies to rethink their pipelines and programmes, for me this year, the statement was: ‘Failure is not an option’ from Steven Bloom, VinceRx. While not new, it sums up the current general mood and highlights an urgent call for action: To get even better at every aspect of what we are doing. Allowing to ‘Fail a programme early’ for commercial reasons is still not practiced enough for lack of commercial insight in the early stages of asset development.

2. The fallout from IRA so far, -13% for Part D drugs net but ‘on average’

IRA: While most presentations and panels covered this topic, there is still uncertainty about how this will play out in detail. The challenge IRA poses can seem somewhat overstated, while for individual products it can be substantial. ~80 Part B and Part D drugs will be subject to mandatory maximum fair price rebate negotiations by 2030. However, analysis of the first 10 drugs subject to rebate negotiations shows that the net impact, on average, is approx. -13% after IRA vs. rebates, and this is applicable only to the Part D portion of the payer mix. So, whether IRA will affect you or not will be on a case-by-case analysis.

3. AI: Too fast too soon – is it the end of the honeymoon period?

AI: Comments such as ‘too fast too soon’ echoed through some of the icebreaker exercises. Others referenced AI as the silver bullet that will help the industry to get better at what it is doing. The truth lies probably somewhere in the middle and, notably, as is often the case with AI, it is not always clear if we talk about AI in drug discovery and disease diagnosis or AI and machine learning in analytics and market research or even genAI and LLMs.

4. The traditional LCM model is dead

Another thread that weaved itself through many panels covering TPP development, commercial strategy, pricing and HEOR was the call for more commercial insight and identification of critical value elements earlier in the drug development process together with the courage, if needed, to fail early. The (early) NPP voice is critical for this job and, making sure that it comes across loud enough. And, leveraging multi-indication potential in post-IRA times requires close and early collaboration between NPP and R&D teams. In this sense the traditional LCM model is changing.

5. Forecasting: Building consensus around assumptions is the hardest part

As the LCM model is changing in line with shorter ROI times and potential price pressure from IRA, forecasting processes need to adapt. It was concluded that consensus building around assumptions is the hardest part. The forecasting process is not static and finding the right update frequency, the right tools or platforms is very much driven by individual market characteristics, the stage of the programme and the size of the organisation. While the future of long-term strategic forecasting may one day be algorithm/AI based with much less PMR input, the present reality is that this future is not yet there and that forecast structure and transparency and human factors of how it is being delivered to senior management play a far greater role in the success of a programme than any forecasting tool.

Get in touch
Erik Holzinger. CEO, groupH
erik.holzinger@grouph.com