Artificial intelligence in a pharmaceutical company

Programme

Day 1

AI tools in the daily work of a pharmaceutical company

1. Artificial intelligence in the work of a pharma company: basic understanding

• What generative artificial intelligence is and how it differs from familiar automation and BI tools.
• How AI is applied at pharmaceutical companies around the world: marketing, medical communications, regulatory affairs, pharmacovigilance, commerce, finance.
• Which tasks of a pharma company can already be partially handed over to AI today, and which require mandatory human involvement.
• The limits of AI applicability in a regulated industry: where AI helps, where it requires verification, and where its use is limited by internal and external requirements.
• Principles of working with AI: setting the task, context, verifying the result, safe handling of confidential information.

2. Preparing presentations and materials for management with AI

• How AI helps to quickly prepare a presentation structure for a given audience: the management board, partners, medical representatives, regulators.
• Generating draft slides, highlighting key messages, selecting wording for the audience.
• Preparing accompanying texts, speaker notes and talking points for presentations.
• Using AI to adapt one presentation for different formats: a board meeting, an external partner, a doctor, a pharmacy chain.
• Practice: participants prepare a real draft presentation on their current task.

3. Preparing reporting and analytical materials

• Using AI to consolidate data from several documents and sources into a single report.
• Preparing management summaries, explanatory notes and comments on indicators.
• Analysing tables and data arrays with AI: identifying deviations, forming conclusions, preparing decision options.
• Forming reporting for different levels of recipients: operational, management, strategic.
• Practice: participants prepare a fragment of a real report based on their own data.

4. Working with documents, regulations and corporate information

• Using AI to quickly extract the essence from long documents: regulations, standards, regulatory requirements, internal orders.
• Preparing meeting summaries, minutes, task lists and assignments.
• Comparing documents, finding contradictions and inconsistencies in materials.
• Preparing memos, requests and standard internal correspondence.
• Principles of safe work with internal information when using AI.

5. First-day practice

• Participants identifying their own recurring tasks in which AI gives a quick effect.
• Reviewing typical tasks of a pharma company by department: where using AI pays off already in the first month.
• Forming an initial list of AI tools and scenarios for the participants' specific functions.
• Discussing expectations, limitations and rules for the safe use of AI in the company.

Day 2

AI tools in the functions of a pharmaceutical company and preparing for implementation

1. AI in the work of the commercial block and the sales department

• Preparing materials for visits to doctors and working with pharmacy chains.
• Sales, assortment and customer base analytics using AI.
• Forming individual commercial proposals and accompanying materials.
• Preparing analytical notes by territory, customer and product line.
• Working with objections, preparing scripts, adapting communications for different customer types.

2. AI in marketing and external communications

• Preparing content for medical representatives, educational materials, presentations for doctors.
• Analysing competitors, market overviews, preparing analytical digests.
• Preparing materials for launching new drugs and supporting the product portfolio.
• Adapting materials for different audiences while complying with industry requirements.

3. AI in regulatory and supervisory functions

• Working with documents for drug and price registration: preparing drafts, checking completeness, structuring information.
• Applying AI in pharmacovigilance tasks: classifying enquiries, preparing draft reporting forms, monitoring deadlines.
• Using AI to track changes in the regulatory environment and quickly analyse new requirements.
• The limits of AI application in regulated processes and mandatory human control.

4. AI in logistics and finance

• Analysing balances, shelf life and batch movement with AI support.
• Preparing requests, approvals and accompanying documents.
• Consolidating financial data, preparing management reporting, explaining budget deviations.
• Automatically forming comments on indicators and options for management decisions.

5. Integrating AI into the company's processes and risks

• How AI can interact with corporate systems: accounting systems, CRM, document databases, reporting systems.
• Practical integration scenarios without a complex overhaul of processes.
• Risks and limitations: generation errors, data leakage, non-compliance with industry requirements.
• Rules for the safe, ethical and controlled use of AI in a pharmaceutical company.
• The human role in each process: where AI acts independently, where approval is required, where it is prohibited without verification.

6. Second-day practice

• Reviewing participants' specific processes that can be simplified with the help of AI right now.
• Building a scheme for using AI in the chosen process: input data, actions, control, result.
• Identifying quick implementation points where a first noticeable result can be obtained.
• Forming a list of AI tools and scenarios for a specific department's tasks.

Expected training outcomes

• A comprehensive understanding of the modern capabilities of artificial intelligence for a pharmaceutical company.
• Confident application of AI tools in preparing presentations, reporting and analytical materials.
• An understanding of which AI solutions are applicable in each company function: the management board, commerce, marketing, logistics, pharmacovigilance, registration, finance, sales.
• Knowledge of the rules for safe work with AI, the limitations and mandatory human control in regulated processes.
• A ready-made initial list of tasks and tools that can be started using immediately after the training.
• An understanding of the possibilities of AI agents as the next step in developing the company's AI environment.