Billions of underserved healthcare customers rise to demand their share in the new wave of pharmaceutical products. While in the West the population ages, and people double their prescription medicine consumption every 20 months through the last 7 years of their lives.
Extensive innovation is called for both in the effort to come up with new drugs, and in the effort to manufacture the growing number of generic drugs in such cost effective way that the poorest will afford them -- and doing all that while keeping the pharmaceutical industry thriving.
To meet this challenge, having applied the InnovationSP methodology, the resulting conclusions are surprising:
AI stands to disrupt Big Pharma. The innovation bottleneck for new drug development is the large number of promising yet eventually disappointing molecular candidates for new medicines. AI, using ever smarter inference engines (e.g. BiPSA) will zero in on high-probability candidates. Such smart inference engines are a brain child of smart and creative individuals that work in small startups, not in big pharma.
Such startups have joined with human testing facilities in the developing world where the regulatory climate is easier, and will then auction off their products to big pharma that will be left to package, promote and market the new medicine.
On the production front, we see dramatic innovation in multi-use material engineering facilities, ground breaking chemical processing that can operate on a small scale and undercut the cost of traditional industrial construction. E.g. a new US patent (11,745,153) creates super accurate versatile mixing, pipe-reactors, while it operates on new principles for phase and ingredient separation.
Here too, small startups are being set up to serve the underserved healthcare customers community.
More than any time in the past, the pharmaceutical industry stands to benefot from application of the InnovationSP platform, to meet the mounting challenges ahead.