FAQ

Everything you need to know about Pharmatech AI.

Frequently Asked QuestionsCompany Overview

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This category covers the mission, vision, unique selling points, team, and milestones of Pharmatech AI, providing a foundational understanding for investors.
Q1: What is Pharmatech AI's mission?
Pharmatech AI’s mission is to revolutionize drug discovery using artificial intelligence, specifically focusing on pain therapy, natural product research (especially cannabinoids), and nanomedicine. By leveraging their proprietary AI Multi-Drug Interaction Predictor (AI-MDIP), they aim to make the development of new drug combinations faster, more cost-effective, and more precise. Traditional drug development is expensive and time-consuming, often costing billions and taking over a decade, as noted in the whitepaper citing the Tufts Center for the Study of Drug Development (2023). Pharmatech AI addresses these challenges through a comprehensive R&D pipeline that integrates data collection, AI prediction, and validation, with a particular emphasis on cannabinoid-based therapies.
Q2: What is the vision of Pharmatech AI?
The vision of Pharmatech AI is to fundamentally transform drug research through AI and establish itself as a global leader in cannabinoid-based therapy development. They strive to significantly reduce development times and costs using AI-MDIP and data from their MDIP Practical Laboratory Grow. Their goal is to create innovative therapies for pain management, neurodegenerative diseases, and other medical needs by harnessing the synergies of cannabinoids. Through strategic partnerships with pharmaceutical companies and academic institutions, they aim to accelerate R&D and solidify their position in precision medicine, all while committing to sustainable and environmentally conscious research practices.
Q3: What makes Pharmatech AI stand out in the market?
Pharmatech AI boasts four key USPs:
  • AI Multi-Drug Interaction Predictor (AI-MDIP): An advanced AI model using Graph Neural Networks and Transformer architectures to predict interactions between small organic compounds, including complex cannabis actives, targeting at least 250,000 molecular interaction examples, ideally 5 million, with 50,000 cannabis-specific.
  • Exclusive Cannabis Data: Generated from their MDIP Practical Laboratory Grow, providing over 15,000 data points per cycle, ensuring data sovereignty from seed to analyzed flower, completed in January 2025.
  • Sustainable Research Center: A 60-hectare campus in Mecklenburg-Vorpommern with a 55 MWp photovoltaic system generating 55 GWh annually, ensuring energy self-sufficiency and a positive CO2 footprint.
  • Focused Research Areas: Concentration on pain therapy, natural product research, and nanomedicine, addressing large international markets with specific applications in predicting interactions of THC, CBD, and other compounds.
Q4_ Who is the core team and what are their backgrounds?
The core team includes:
  • Ercan Hayvali, M.Sc., CEO: An economist and AI research manager with expertise in IT analysis, AI research, and blockchain solutions, holding two master’s degrees from the University of Kassel.
  • Christian Tonn, Director of Research Cultivation Facilities: A market access manager with experience in the pharma and cannabis sectors, founder of CeBiol GmbH.
  • Miguel Martinez Bermudez, Lead Cannabis Lab Analyst: A pharmaceutical extraction expert, leading Swiss Cristal Lab AG, focusing on cannabis extract analysis.
  • Sebastian Reifegerste, Head of Cannabis Research Alliances and Market Strategy: An international cannabis expert with a pharmaceutical background, involved in European cannabis industry development.
  • Mert Enginer, Data Center Infrastructure Manager: An IT infrastructure manager with startup experience, specializing in cloud and data center management.
  • Philipp Bösch, Agricultural Research Director: A cannabis cultivation expert with over a decade of experience, optimizing production under GACP standards.

Frequently Asked QuestionsTechnology and Innovation

This category focuses on the AI-MDIP, its functionality, uniqueness, and integration with cannabis research, emphasizing its novelty.
Q5: What is the AI Multi-Drug Interaction Predictor (AI-MDIP)?
The AI Multi-Drug Interaction Predictor (AI-MDIP) is a cutting-edge AI model developed by Pharmatech AI to predict interactions between small organic compounds, including complex mixtures like cannabis extracts. It employs Graph Neural Networks (GNNs) to represent molecules as graphs and Transformer architectures to model interactions between multiple compounds. This allows AI-MDIP to forecast whether drug combinations will have synergistic, antagonistic, or toxic effects, thereby accelerating the discovery of effective and safe medication combinations, particularly for cannabinoid-based therapies.
Q6: How does AI-MDIP work?
AI-MDIP operates by first representing each molecule as a graph, with atoms as nodes and chemical bonds as edges. GNNs process these graphs to generate embeddings that capture the chemical and structural properties of the molecules. These embeddings are then fed into a Transformer encoder, which models the interactions between multiple molecules by considering their combined effects. Finally, a multi-layer perceptron (MLP) processes the output to predict interaction outcomes, such as synergy scores or toxicity levels. This sophisticated architecture enables precise predictions of complex drug interactions, validated through the MDIP Practical Laboratory Grow.
Q7: What makes AI-MDIP unique compared to other AI models in drug discovery?
AI-MDIP stands out due to its specialized focus on multi-drug interactions, particularly with complex natural compounds like cannabinoids. While many AI models concentrate on single drug-target interactions or protein folding, AI-MDIP is designed to predict how multiple drugs interact with each other and with biological systems. Additionally, the integration of proprietary cannabis data from the MDIP Practical Laboratory Grow provides a unique advantage in exploring therapies not well-covered in existing datasets like PubChem or DrugBank. The combination of GNNs and Transformers allows for a more nuanced modeling of molecular interactions compared to traditional machine learning approaches, positioning Pharmatech AI at the forefront of AI-driven drug discovery.
Q8: What are the main research areas of Pharmatech AI?
Pharmatech AI focuses on three primary research areas:
  • Pain Therapy: Developing innovative treatments for pain management, leveraging cannabinoid synergies and combinations with other analgesics, addressing the opioid crisis with non-opioid alternatives.
  • Natural Product Research: Exploring the therapeutic potential of natural compounds, with a particular emphasis on cannabinoids like THC, CBD, CBG, and terpenes, focusing on the Entourage Effect.
  • Nanomedicine: Investigating the use of nanotechnology to enhance drug delivery and efficacy, including the encapsulation of cannabinoids in nanoparticles for targeted therapy, particularly for bacterial infections.
Q9: How does Pharmatech AI integrate cannabis research into its technology?
Pharmatech AI integrates cannabis research through its MDIP Practical Laboratory Grow, where cannabis is cultivated under controlled conditions to produce specific cannabinoid and terpene profiles. The laboratory generates detailed chemical profiles and biological test data, which are used to train the AI-MDIP model, ensuring data sovereignty from seed to analyzed extract. This proprietary data allows AI-MDIP to make accurate predictions about cannabis-based therapies and their interactions with other drugs, enabling the development of personalized and effective treatment options, with each cycle adding over 15,000 data points to the database.

Frequently Asked QuestionsOperations and Facilities

This category details the research location, facilities, and sustainability practices, emphasizing the uniqueness of the MDIP Practical Laboratory Grow and the sustainable campus.
Q10: Where is Pharmatech AI's research facility located?
Pharmatech AI’s research facility is located in Mecklenburg-Vorpommern, Germany. This location was chosen for its supportive regulatory environment, access to skilled professionals, and proximity to European research hubs. The campus spans 60 hectares and includes 120,000 square meters of indoor space dedicated to various research and development activities, making it a strategic hub for innovation.
Q11: What are the key features of the research facility?
The research facility boasts several key features:
  • Computing Centers (60,000 m²): Housing powerful computing resources for AI model training and data analysis, equipped with modern GPUs and TPUs.
  • Laboratories (20,000 m²): Equipped for chemistry, biology, and cell research with automated systems for high-throughput screening, enhancing efficiency.
  • Design and Development Spaces (20,000 m²): For collaborative work on drug design and development using AI tools, fostering interdisciplinary innovation.
  • Preclinical and Clinical Testing Departments (10,000 m²): For validating drug candidates through rigorous testing, optimizing study designs with AI.
  • Sustainability and Recreation Areas (10,000 m²): Including green spaces and facilities to promote employee well-being, aligning with ESG goals.
Q12: What is the MDIP Practical Laboratory Grow?
The MDIP Practical Laboratory Grow is a 200-square-meter facility dedicated to vertical cannabis cultivation integrated with AI research, completed in January 2025. It allows Pharmatech AI to grow cannabis under controlled conditions, analyze its chemical profiles, and generate proprietary data for AI-MDIP training. The lab uses advanced technologies such as adaptive LED lighting, intelligent irrigation, and CO2 management to optimize growth and data collection, producing over 15,000 data points per cultivation cycle, ensuring complete data sovereignty.
Q13: How does Pharmatech AI ensure sustainability in its operations?
Pharmatech AI ensures sustainability through its 55 MWp photovoltaic system, which generates approximately 55 GWh of electricity annually. This renewable energy source powers the entire facility, achieving energy self-sufficiency and reducing the carbon footprint. The center’s design incorporates eco-friendly practices and materials, aligning with the company’s commitment to environmental responsibility and meeting ESG criteria, reducing GPU operating costs by up to 70%.
Q14: What are the future expansion plans for the research facility?
Future expansion plans for the research facility include:
  • Expanding the MDIP Practical Laboratory Grow: Doubling the cultivation areas to grow more cannabis varieties under varied conditions and generate additional data for AI-MDIP.
  • Establishing Specialized Laboratories: For cutting-edge technologies like CRISPR-based optimization of cannabinoid biosynthesis pathways, enhancing research capabilities.
  • Enhancing Computing Infrastructure: Investing in high-performance GPU clusters to handle larger datasets and more complex AI models, supporting scalability.
  • Developing On-Site Production Facilities: To accelerate the transition from research to small-scale production of promising drug candidates, reducing time-to-market by up to 40%.

Frequently Asked QuestionsInvestment Opportunities

This category focuses on the PCH token, its utilities, and investment mechanisms, ensuring all investor-related information is covered to attract potential stakeholders.
Q15: What is the PCH token and what is its purpose?
The PCH token is a utility token that serves multiple functions within the Pharmatech AI ecosystem. It allows holders to access and purchase research results, participate in governance decisions, and earn rewards through staking mechanisms. The token is designed to align the interests of the community with the project’s success, providing both utility and potential financial benefits, with a total supply of 1,000,000,000 tokens and no future inflation.
Q16: How can investors participate in the PCH token sale?
Investors can participate in the PCH token sale through various fundraising phases:
  • Pre-Seed Round: Early investment opportunity at $0.0135 per token, with 4% allocation (40M tokens).
  • VC Round: For venture capital investors at $0.0155 per token, with 6% allocation (60M tokens).
  • KOL Round: For key opinion leaders at $0.0250 per token, with 4% allocation (40M tokens).
  • Public Round: Open to the public at $0.0325 per token, with 7% allocation (70M tokens), planned for Q4 2025.
Each round has specific allocations and vesting schedules to ensure fair distribution and long-term commitment.
Q17: What are the benefits of holding PCH tokens?
Holding PCH tokens offers several benefits:
  • Staking Rewards: Token holders can stake their PCH to receive a share of the platform’s revenues, with 70% of fees going to a revenue pool for qualified stakers.
  • Governance Participation: Staked tokens grant voting rights in key decisions affecting the project’s development, executed via on-chain snapshot voting.
  • Access to Exclusive Features: Tokens can be used to access premium features or data on the platform, such as IP licensing and patent auctions.
  • Potential Value Appreciation: Through buyback and burn mechanisms, the token supply decreases over time, potentially increasing the value of remaining tokens, with 10% of revenues allocated for buybacks.
Q18: How does the revenue sharing model work for PCH token holders?
The revenue sharing model allocates 70% of all platform fees to a revenue pool, which is distributed quarterly to qualified token holders who have staked their PCH tokens. The distribution is based on the amount staked and the duration of staking, with longer staking periods offering higher rewards through multipliers (e.g., 1.5x for 12 months, up to 3x for 36 months). This model ensures that token holders directly benefit from the project’s financial success, with expected cash flows of $84 million annually by 2028 from platform revenues.
Q19: What is the token distribution and vesting schedule?
The total supply of PCH tokens is 1,000,000,000, distributed as follows:
  • Core Team: 8% (80M), 0% at TGE, 12-month cliff, then linear release over 36 months.
  • Advisors: 3% (30M), 0% at TGE, 6-month cliff, linear release over 12 months.
  • Pre-Seed: 4% (40M), 0% at TGE, 2-month cliff, linear release over 12 months.
  • VC Round: 6% (60M), 5% at TGE, 1-month cliff, rest linear over 12 months.
  • KOL Round: 4% (40M), 10% at TGE, no cliff, rest linear over 12 months.
  • Public Round: 7% (70M), 15% at TGE, no cliff, rest linear over 12 months.
  • Partnerships/Development: 10% (100M), 3% at TGE, rest linear over 12 months.
  • Marketing Ecosystem: 15% (150M), 5% at TGE, rest linear over 12 months.
  • Treasury & Liquidity Pool: 43% (430M), 40% at TGE, rest linear over 12 months.
This ensures long-term alignment and commitment from stakeholders, with the first exchange listing at $0.0325 per token, aiming for a fully diluted market cap of $32.5 million at TGE.