To align our business model for long-term success, we conducted an in-depth market analysis early on, with results that confirmed and accelerated our strategic direction. A five-member research team conducted over 200 in-depth interviews with stakeholders, from pharmacists in Munich to pain specialists in Boston. The findings were clear:
1. High Dissatisfaction with Existing Therapies
82% of surveyed physicians expressed dissatisfaction with current pain therapies.
“Patients are demanding alternatives to opioids, but the data on cannabinoids is too limited,” reported a neurologist from Boston.
There is a massive unmet need for more effective and safer therapies, particularly for chronic pain, neurodegenerative diseases, and inflammatory conditions.
2. Market Gap: No Competitor Controls the Entire Value Chain
Our competitive analysis revealed: No company combines AI-driven drug discovery with proprietary cannabis cultivation and sustainable production.
Most players focus either on traditional pharmaceutical research or generic cannabis products, without precise data analytics or AI optimization.
3. Cannabinoid Research is Understudied—We’re Closing the Gap
While the global medical cannabis market is projected to reach $41.4 billion by 2030 (CAGR: 13.6%), there is little systematic research on:
Synergies between cannabinoids (THC, CBD, CBG) and classical drugs (e.g., ibuprofen + THC).
Entourage effects (interactions between terpenes and cannabinoids).
Personalized therapies via AI-optimized dosing.
“That was the moment we realized we couldn’t just be researchers, we had to be producers too,” explains Cultivation Lead Miguel Martinez.
Our Solution: Pharmatech AI as a Pioneer in Data-Driven Cannabinoid Research with AI-MDIP.
Based on these insights, we accelerated and focused our company’s founding with a unique approach:
- Proprietary Cannabis Cultivation in the MDIP Lab Grow
200 m² high-tech facility with fully automated control (IoT sensors, adaptive LED lighting, CO₂ circulation).
50,000+ proprietary data points per cycle (chemical profiles, growth conditions, biological assays).
- AI Model “AI-MDIP” for Precise Drug Interaction Predictions
Graph Neural Networks (GNNs) + Transformer architectures analyze cannabinoid-drug combinations.
Goal: 250,000–5 million trained interactions, including 50,000 cannabis-specific datasets.
- Sustainable, Energy-Autonomous Research
60-hectare campus in Germany with a 55 MWp photovoltaic system (55 GWh/year).
Cost savings through green energy: Up to 70% lower GPU operating costs for AI training.
Why This is a Game-Changer
Pharmatech AI represents a true game-changer in pharmaceutical research by being the first company to successfully integrate AI-driven drug discovery with proprietary cannabinoid cultivation and sustainable production in a fully closed-loop system. Our first-mover advantage is undeniable because no competitor currently possesses comparable proprietary datasets or our unique infrastructure combining a high-tech cultivation facility with cutting-edge AI analytics.
This vertically integrated approach gives us unprecedented regulatory confidence, as our standardized data collection from plant genetics through to active compounds ensures perfect reproducibility, a critical factor for clinical approvals. The business model is designed for rapid scalability, with dual revenue streams from therapy licensing to major pharma partners (projected $150-300M by 2027) and our AI-MDIP platform offered as SaaS to biotech firms starting in 2026. When we combine the massive unmet medical needs in pain management and neurology with the complete lack of direct competition and our technological leadership, Pharmatech AI is uniquely positioned to capture significant value in the $2.3 trillion global pharmaceutical market.
As CEO Ercan Hayvali notes, “Our comprehensive market research didn’t just validate our approach – it demonstrated we’re several years ahead of any potential competition in this space.” With our research campus operational, initial cultivation cycles completed, and AI validation underway, we’re not just talking about potential – we’re delivering on it.