Price water house cooper competing presentation

Competition ppt

1. Executive Summary Approach Way Forward for Dolocon Solutions to be Implemented (Manufacturing) Use shared warehousing space. This can help to reduce costs and improve efficiency Local manufacturing.  This can help to reduce transportation costs and environmental impact. Improvise manufacturing.  This means using new and innovative technologies to improve the manufacturing process. Solutions to be Implemented ( in Drug development & research) AI can automate drug discovery: Speed up and reduce costs AI can personalize drug therapy:  Improve effectiveness and reduce side effects AI can improve drug safety:  Identify risks and side effects early. Solutions to be Implemented ( in Supply Chain) Use shared warehousing space:  This can help to reduce costs and improve efficiency. Local manufacturing:  This can help to reduce transportation costs and environmental impact Improvise manufacturing:  This means using new and innovative technologies to improve the manufacturing process Alternative Trade Routes To be aware of the risks and opportunities associated with each option To u nderstand the market access and cost implications of each option . To Make a decision that is right for DoloCon . 3-year roadmap for DoloCon based on vision shared by CXOs and pharma industry trends to position DoloCon as a leader in the next pharma revolution.  Tech-based solutions looking into the landscape of the latest and upcoming technologies (financially and operationally viable) to DoloCon which will help them achieve their overall objective. Conduct an opportunity assessment of alternative supply network landscape and trade routes focusing on the supply chain model . 1

2. Sector Overview Market growth Trend Of the Industry Projected Growth To grow at a CAGR of 5.4% from 2021 to 2028, a value of USD 432.12 billion by 2028  The EIMP is a public-private partnership that is designed to accelerate the development of pharma Industry The European pharmaceutical industry is the second largest in the world, after the United States invests over €40 billion in research and development each year , generates over €300 billion in revenue each year , exports over €100 billion Industry Trends Key Observations The cost of drug development is increasing. The time to market for new drugs is increasing . The number of new drug approvals is decreasing The use of technology in the pharmaceutical industry is increasing The need for collaboration is increasing U se of D igitization in drug development and supply chain, manufacturing. M onitor, record, and assess processes to enhance sustainability performance & reporting Increasing Investments: The global market for AI in the pharma industry is expected to reach $24.6 billion by 2027, growing at a CAGR of 42.8% from 2022 to 2027. Innovations: Personalized medicine, Gene therapy,3D P rinting, Artificial intelligence ,Blockchain.  Need of the hour : Improved efficacy and safety: Natural products, Reduced costs, Improved speed to market. The new method of Big Data Analysis is related to new algorithms based on historical data, which can be used to identify quality problems and for reducing the failure of products 2

3. Digital Ecosystem Integration: Integrate platforms for seamless product lifecycle management. Improve customer experience with personalization and engagement. AI-Driven Innovation: Create AI hub for innovation in drug processes. Investigate AI's role in compliance, safety, and predictions.. Global Brand Building: Boost DoloCon's brand via creative marketing, partnerships. Improve patient engagement with AI health tools. Expand to new regions using tech for market entry. Technology-Infused Distribution Use AI for resilient, cost-effective supply chain. Tech-driven distribution for visibility and efficiency. Partner with logistics for smooth global operations. Roadmap Year 1 Year 2 Supply Chain Resilience and Diversification Analyze supply chain vulnerabilities, especially China-based dependencies. Diversify sourcing for key APIs and components. Partner with suppliers across varied regions. Pilot projects to test alternative supply chains. Technology-Driven Efficiency Apply AI for cost-effective demand forecasting and production planning. Integrate real-time IoT data for better manufacturing control. Deploy automation for streamlined operations. Operational Excellence: Building Resilience and Diversifying Supply Chain Transformation and Sustainability: Leadership in Digital Healthcare Innovation and Expansion: Technological Advancements and Market Penetration Year 1 Year 3 Market Expansion and New Product Development Study regulations and incentives for smooth market entry. Create teams for market exploration and entry strategies. Innovate drugs using AI-driven discovery. Digital Ecosystem Development Launch AI platform for personalized care tools and treatment advice. Create tech-driven patient engagement for better experience and adherence. Implement data solutions for privacy and compliance. Advanced R&D and Clinical Trials Partner with tech startups for AI-driven drug discovery. Use data for smarter clinical trials and patient care. Pursue precision medicine for tailored treatments.. AI-Enhanced Marketing: Build AI models for targeted marketing campaigns. Launch AI tools for doctor diagnosis & treatment. Partner with tech firms for advanced marketing analytics. Sustainable Growth and Profitability: Track and enhance initiatives for efficiency and growth. Use AI for robust financial planning and allocation. Diversify sourcing to manage risks in supply chain. Thought Leadership and Collaboration Join conferences to highlight tech progress. Partner with academia and tech for pharmaceutical innovation. 1 2 3 Strong Supply Chains, Tech Innovation - Path to Success Tech Innovation, Digital Leadership - Transforming Health Sustainablyv Empowering Health: Resilient Supply, Sustainable Transformation 3

4. Dolocon Value Chain Interaction with AI 4 Applications of AI Pharmaceutical product management Drug Discovery Pharmaceutical product development Market positioning Market prediction and analysis Product Costing Drug design Drug screening Market positioning Product Costing Drug – protein interaction Bioactivity prediction Product Costing Drug – protein interaction Aid in deciding suitable excipients Ensuring in-process specification compliance Monitoring and modifying development process Clinical trial design and monitoring QA and QC Pharmaceutical manufacturing Subject enrolment/selection Market prediction and analysis Monitoring of trial Understand critical process parameters Guide future production cycle Regulation of in-line quality Ensure QA with aid of ELN and other techniques Automated manufacturing Correlating manufacturing errors to set parameters Personalized manufacturing Quantum Computing Deep Learning Predictive Analytics Computational Chemistry Optimization Algorithms Predictive Modelling Robotics and Automation Model complex molecular structures more accurately for drug discovery. Applied to analyze complex molecular interactions and predict drug properties. Used to optimize manufacturing processes, predict equipment failures, and ensure consistent quality. Utilized in high-throughput screening, compound synthesis Chemical interactions and predicting the behavior of compounds in various formulations. Advanced Analytics Analyzing data from various sources to optimize formulation development and stability testing Natural Language Processing Analyzing supplier contracts, regulatory documents, and other text data for compliance and risk assessment Optimize distribution routes, minimize transportation costs, and maintain cold chain integrity Predicting potential quality issues based on historical data and process parameters. DRUG DESIGN Manufacturing Formulation Supply Chain QA/QC A I Technologies in Value Chain

5. Recommendation – AI Adaptation in Drug Discovery & Formulation Striving to revolutionize the pharmaceutical industry by seamlessly integrating AI-powered innovations for advanced drug discovery, formulation, and operations, while pioneering cutting-edge technologies to lead in innovation and deliver precision medicine through digitally optimized processes. Primary Goal Use of AI/ML in Drug Design and Formulation AI Models in Pharmaceuticals: Supervised Learning & Unsupervised Learning models are use  to enhance different aspects of the process.   AI for Drug Discovery: V irtual screening, target prediction, molecular design, and clinical trial optimization 5 Machine Learning Deep Learning Clustering Dimensionally Reduction Utilizing supervised learning algorithms for predicting novel drug candidate properties through learned patterns from known compounds, enhancing drug discovery efficiency ML identifies drug targets through genetic, recognizing patterns that highlight potential investigational targets Supervised learning aids pharmaceutical manufacturing with predictive maintenance and quality control , foreseeing equipment failures, and process anomalies from data. Predict patient outcomes based on medical data, model can learn to category patient into different disease. Clustering algorithms categorize data by similarities, revealing clusters in pharmaceutical datasets like genes, chemicals, or patients, aiding target discovery and patient stratification. Aid in target identification, patient stratification, and identifying distinct classes of compounds or diseases. Methods like PCA and t-SNE simplify high-dimensional data in pharmaceutical applications, aiding visualization, feature identification, and decision-making across gene, drug, and imaging data. Used in gene expression data, drug activity profiles, or imaging data AI in drug Design AI in polypharmacology AI in chemical synthesis AI in drug repurposing AI in drug screening AI in drug discovery Predicting 3D structure of target protein Predicting drug-protein interactions AI in determining drug activity AI in de novo drug design Designing biospecific drug molecules Designing multitarget drug molecules AI in prediction of reaction yield AI in prediction of retrosynthesis pathways Developing insights into reaction mechanisms AI in designing synthetic route Identification of therapeutic target Prediction of new therapeutic use Prediction of toxicity Prediction of bioactivity Prediction of physiochemical property Identification and classification of target cells

6. End to End Visibility Inventory Management Intelligent Automation Optimizing Predictive Mgt. AI-augmented control towers provide advanced decision-making systems by managing the data in real time. Point-to-point visibility across the whole supply chain will enable companies to become more efficient by rapidly responding to and mitigating disruptions. AI tools can mine and analyze data from multiple sources to detect patterns and potential anomalies to generate accurate demand forecasts. Cold chain transportation technology can be integrated with tracking software to ensure the effectiveness of therapeutics. Adoption of AI tools, computer vision, into an Industry 4.0 and IoT platform will be the key to minimizing human error. Automation can combines RPA and machine learning that can mimic human interaction and make advanced decisions based on the outputs of those robotic inputs. AI technologies can find patterns and interdependencies between variables that would otherwise be missed by traditional methods ML can help manufacturing assets to be ready when needed by preventing unplanned downtime. . Recommendation – AI-powered technologies in the biopharma supply chain To identify the growth opportunities and tech based solution in the biopharma supply chain. Objective A roadmap for implementing an intelligent supply chain Applications of AI-powered technologies in the biopharma supply chain Benefits of the Framework Concepts used from Industry 4.0 6 To reduce the risks associated with integrating new digital technologies and platforms, the approach of manufacturers across industries is to start with pilot projects and evaluate the use of data and achievements before scaling up. Win-win approach between industry and regulators Acquire and build internal skills and talent Build a blueprint of your data architecture Start small, scale fast and think big Identify internal cost and value drivers Collaborate and learn from other industries CargoSense research suggest 30 per cent of discarded pharmaceuticals can be attributed solely to logistics issues Google Cloud Platform, Microsoft Azure’s AI platform technology, Amazon Web Service (AWS) can be utilized to make manufacturing process more efficient. Dolocon can learn from other sectors by acquiring their expertise and adopting their models Deloitte research found that the biggest issue most companies across industries need to overcome to implement DSNs and use AI effectively is finding and training the right employees Dolocon can enhance compliance and efficiency by integrating systems, streamlining processes, and valuing regulatory functions strategically

7. Improvise Manufacturing Economics of Scope Increasing tech leverage Industry4.0 Economics of Scale Joint Manufacturing Economics of Scope Solution for Cost Optimized Manufacturing Manufacturing problems in Europe Pharma companies Stringent Regulatory Environment: Complex and varying regulations across European countries increase the time and cost of obtaining approvals and ensuring compliance, impacting manufacturing processes. High Production Costs and Labor Expenses: Elevated labor costs and stringent labor regulations contribute to higher manufacturing expenses in Europe, affecting competitiveness on a global scale. Supply Chain Vulnerabilities and Dependency: Reliance on a limited number of suppliers and countries for critical raw materials and APIs exposes European companies to supply chain disruptions and shortages. Slow Adoption of Advanced Technologies: European pharma companies have been slower in adopting Industry 4.0 technologies, hindering operational efficiency, flexibility, and innovation. Complex Pricing and Reimbursement Systems: Varied pricing and reimbursement mechanisms across European countries create challenges in managing product pricing and forecasting revenues accurately. 7 Pharma company 4 Pharma company 3 Pharma company 2 Pharma company 1 Manufacturing site Manufacturing site Manufacturing site Manufacturing site Shared warehousing space Local manufacturing sites . Physical joint warehouse Pharma company 1 Pharma company 2 Pharma company 3 Entire site and indirect services used Entire site and indirect services used Entire site and indirect services used Joint Manufacturing Facilities in Pharma Industry Features and Benefits: Cost Sharing: Collaborative setup reduces individual financial burden. Efficiency: Enhanced efficiency through shared services and streamlined operations. Challenges and Considerations: Strategic Alignment: Requires negotiation and compromise for mutual goals. Long-term Commitment: Ongoing investment commitment even during strategic shifts. Leveraging Industry 4.0 and Lean Manufacturing Data-Driven Optimization: Utilizing data analytics, AI, and IoT sensors to gather real-time data from manufacturing processes. Enhances decision-making by identifying inefficiencies . Digital Twins for Simulation: Creating virtual replicas of manufacturing processes to simulate and optimize operation reducing trial and error, and improving process efficiency . Lean manufacturing for better Quality Control Enhancement: Implementing AI-powered image recognition for real-time quality control during production. Detects defects and ensures consistent product quality, reducing waste and rework . Local manufacturing sites Solution Joint manufacturing and warehouse

8. Alternate Trade Route Options API Manufacturing Formulation Primary Packaging Secondary Packaging Complex Intermediaries Base Specialty Chemical Mainland China Regulatory Starting Material Upstream Chemicals Aluminum China, India, Russia Piperidine France Dibasic calcium phosphate Belgium Microcrystalline cellulose US, Taiwan Wood Pulp US, Canada, Brazil Mineral Acids India, mainland China Povidone US, Germany, China Vinylpyrrolidone US , Germany Hydrogen peroxide Magnesium Stearate China, Japan, US Solvents & Reagents Excipients Primary Packaging Material Ethanol US Plastics Saudi Arabia, Russia, US Primary Packaging Material Paper China, US, Japan To assess the opportunity for alternate sourcing and manufacturing base, we tried to look into the following parameters and have prepared a matrix of options. Geopolitical stability:  This refers to the likelihood of a country experiencing political instability, such as a coup d'état or civil war. A stable political environment is important for businesses because it provides a predictable and secure environment in which to operate. Sustainability:  This refers to the ability of a country to meet its current needs without compromising the ability of future generations to meet their own needs. A sustainable country is one that uses its resources efficiently and minimizes its environmental impact. Market access:  This refers to the ease with which businesses can enter and operate in a country. A country with good market access has a large and growing market, as well as a well-developed infrastructure that makes it easy to do business. Geopolitical risks:  This refers to the likelihood of a country being involved in a major armed conflict or other geopolitical event that could disrupt business activity. A country with low geopolitical risks is one that is not likely to be involved in any major armed conflicts or other geopolitical events. Legal framework:  This refers to the quality of the legal system in a country. A strong legal framework provides businesses with the certainty and predictability they need to operate effectively. Transportation infrastructure:  This refers to the quality of the transportation infrastructure in a country. A good transportation infrastructure makes it easy for businesses to move goods and people around the country. Short term opportunities in the pharma supply chain: Focusing on a hub-and-spoke model, emphasizing localized finished goods production, enhances supply reliability with increased local stockpiling, while comprehensive end-to-end supply chain monitoring bolsters predictive capabilities and risk mitigation. General Pharma Supply Network Opportunity Assessment 8

9. G lobal Hotspot for Sourcing & Manufacturing Souring and Manufacturing Channels that Dolocon can Explore India Vietnam Malaysia Brazil US Canada Define sourcing and manufacturing needs. Identify potential sourcing and manufacturing locations Evaluate potential locations considering factors such as the cost of labor, the availability of raw materials, the quality of infrastructure, and the political and economic stability of the country Select a sourcing location and manufacturing base:  Based on your evaluation, you can select a sourcing location and manufacturing base that best meets your needs Develop a sourcing and manufacturing strategy:  This strategy should include details on how you will source and manufacture your products or services, as well as how you will manage the supply chain Implement your sourcing and manufacturing strategy:  This will involve putting into place the processes and systems necessary to source and manufacture 9 Manufacturing Sourcing

10. Cost Benefit Analysis Alternate Trade Routes Benefit: Reduced transportation costs: Using alternate trade routes can often reduce transportation costs, as they may be shorter or use less expensive modes of transportation. Improved market access: Using alternate trade routes can sometimes improve market access, as they may allow businesses to reach new markets or avoid trade barriers. Reduced environmental impact: Using alternate trade routes can sometimes reduce the environmental impact of transportation, as they may use less fuel or emit fewer pollutants. Risks: Increased transit time: Using alternate trade routes can sometimes increase transit time, as they may be longer or use less efficient modes of transportation. Increased risk of delays: Using alternate trade routes can sometimes increase the risk of delays, as they may be more susceptible to disruptions. Increased risk of damage: Using alternate trade routes can sometimes increase the risk of damage to goods, as they may be transported through less secure or stable regions. The availability of infrastructure and services along the route. The political stability of the countries through which the route passes. The security of the route. The customs and import/export regulations that apply to the route. Drug Discovery & Formulation Benefit: Reduced costs: AI can help to reduce the costs of drug discovery and formulation by automating tasks, such as screening potential drug candidates and predicting their properties. Improved efficiency: AI can help to improve the efficiency of drug discovery and formulation by streamlining the process and identifying potential problems early on. Improved accuracy: AI can help to improve the accuracy of drug discovery and formulation by providing more precise predictions of the properties of potential drug candidates. Personalized medicine: AI can be used to personalize medicine by identifying the right drug for each patient. Improved safety: AI can help to improve the safety of drugs by identifying potential risks and side effects early in the development process. Risks: High upfront costs: The development of AI-based drug discovery and formulation tools can be expensive. Data availability: The development of AI-based drug discovery and formulation tools requires large amounts of data. Bias: AI models can be biased, which can lead to the development of drugs that are not effective for certain populations. This is a risk that must be carefully managed Regulation: The use of AI in drug discovery and formulation is still in its early stages, and there are few regulations governing its use. This could lead to safety concerns and legal challenges.. Manufacturing Benefit: Reduced costs: AI can help to reduce costs in the biopharma supply chain by automating tasks, such as tracking shipments, monitoring inventory levels, and forecasting demand. Improved efficiency: AI can help to improve the efficiency of the biopharma supply chain by optimizing routing, scheduling, and inventory management.. Improved visibility: AI can help to improve visibility into the biopharma supply chain by providing real-time data on inventory levels, shipments, and demand. Increased flexibility: AI can help to increase the flexibility of the biopharma supply chain by enabling rapid response to changes in demand or supply. Improved compliance: AI can help to improve compliance with regulations by tracking and monitoring data. This can help to avoid fines and penalties.. Risks: High upfront costs: The development and implementation of AI solutions in the biopharma supply chain can be expensive. However, the long-term cost savings can outweigh the initial investment. Data availability: The use of AI in the biopharma supply chain requires large amounts of data. This data can be expensive to collect and prepare. Complexity: AI solutions can be complex to develop and implement. This can lead to delays and challenges. Security: AI solutions can be vulnerable to security breaches. This could lead to the unauthorized access or disclosure of sensitive data. Bias: AI models can be biased, which can lead to unfair or inaccurate decisions. This is a risk that must be carefully managed. The use of AI in drug discovery and formulation has the potential to revolutionize the industry. By carefully weighing the benefits and risks, drug developers can make informed decisions about whether to use AI in their work. Overall, the use of AI in drug discovery and formulation has the potential to significantly reduce costs, improve efficiency, and improve the accuracy and safety of drug development. The use of AI in the biopharma supply chain has the potential to significantly reduce costs, improve efficiency, and improve visibility and flexibility. However, there are also some risks associated with this technology, such as high upfront costs, data availability, complexity, security, and bias. By carefully considering the benefits and risks, biopharma companies can make informed decisions about whether to use AI in their supply chains. 10