AI+ Pharma™

Course code: AP1405

Price of the certification exam is included in the price of the course.

Formerly known as AI+ Pharma™

Harness AI in Pharma to speed drug discovery, optimize trials, and enable precision therapies.

Revolutionize Healthcare Expertise with AI+ Pharma Practitioner™ for Smarter, Data-Driven Decisions

Beginner-Friendly Pathway: Ideal for learners and professionals entering the world of AI in pharmaceuticals, offering clear fundamentals and easy-to-grasp concepts
Integrated Learning Experience: Combines core pharma knowledge with intuitive AI tools, real-world case studies, and guided practice to strengthen analytical and operational skills
Industry-Focused Growth: Equips you with practical projects, scenario-based exercises, and actionable insights to help you apply AI in drug development, research, compliance, and patient-centric solutions

Akční cena

140 EUR

169 EUR including VAT

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Course dates
Course description
Target group
Course structure
Prerequisites
Certification

Course dates

Starting date: Upon request

Type: Self-paced

Course duration: 8 hours

Language: en

Price without VAT: 140 EUR Akční cena

	Starting date	Type	Course duration	Language		Price without VAT
	Upon request	Self-paced	8 hours	en	A	140 EUR	Register
G	Guaranteed course
A	Akční cena

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Course description

Bridges AI and Life Sciences:

Connects core AI skills with pharmaceutical R&D, clinical workflows, and regulatory realities to make you truly industry-ready.

Speeds Drug Discovery & Development:

Equips you to apply AI for target identification, molecule screening, and trial optimization, shortening development cycles.

Enhances Decision-Making in Healthcare:

Enables data-driven decisions using AI models for risk assessment, patient stratification, and treatment optimization.

Increases Career Opportunities in Pharma & Healthtech:

Positions you for emerging roles at pharmaceutical companies, biotech startups, CROs, and AI-driven health platforms.

Prepares You for the Future of Precision Medicine:

Builds the skills to contribute to personalized therapies, adaptive clinical pathways, and AI-augmented healthcare ecosystems.

Python
TensorFlow
PyTorch
Scikit-learn
Pandas
NumPy
SQL
Jupyter Notebooks
MLflow
DataBricks
RDKit
DeepChem
Biopython
Hugging Face Transformers for Biomedical NLP
spaCy / Clinical NLP Toolkits
Apache Spark for Healthcare Data
Power BI / Tableau for Clinical Dashboards

Target group

Pharmacy & Life Sciences Students: Learners who want to complement their pharma or biotech background with practical AI skills.

Pharmaceutical & Biotech Professionals: R&D, clinical, or regulatory teams aiming to apply AI in drug discovery, trials, and safety.

Healthcare & Medical Practitioners: Doctors, clinicians, and healthcare managers interested in AI-driven decision support and precision therapeutics.

Data scientists & AI Engineers: Technical professionals looking to specialize in pharma, healthcare analytics, and intelligent drug development pipelines.

Healthtech & Medtech Innovators: Entrepreneurs, product managers, and consultants building AI-powered solutions for pharma, clinical research, and digital health.

Course structure

Module 1: AI Foundations for the Pharma Practitioner

1.1 Core AI & ML Concepts
1.2 Generative AI in Pharmaceutical Workflows

Module 2: AI-Driven Drug Discovery & Molecular Design

2.1 Next-Gen Molecular Drug Design
2.2 AI-Powered Drug Repurposing & Target Identification
2.3 AI for Natural Product & Peptide Discovery

Module 3: AI-Optimized Clinical Trials

3.1 AI-Enhanced Patient Recruitment
3.2 Decentralized and AI-Augmented Trial Operations
3.3 Adaptive Trial Design with AI

Module 4: Precision Medicine, Genomics & Multi-Omics AI

4.1 AI for Multi-Omics Data Integration
4.2 AI-Driven Personalized Treatment & Companion Diagnostics
4.3 AI for Rare Disease & Orphan Drug Development

Module 5: AI in Regulatory Affairs, Medical Writing & Pharmacovigilance

5.1 AI-Powered Regulatory Intelligence
5.2 Generative AI for Medical and Regulatory Writing
5.3 AI in Pharmacovigilance and Safety Surveillance

Module 6: AI Ethics, Governance & Responsible AI in Pharma

6.1 Ethical AI Principles in Pharma
6.2 AI Governance Frameworks and Compliance

Module 7: Emerging Technologies & Future of Pharma AI

7.1 AI + Quantum Computing in Drug Discovery
7.2 AI-Enabled Digital Biomarkers & Wearables
7.3 AI for Sustainable & Patient-Centric Pharma

Module 8: Capstone Project

8.1 Capstone Project 1 – AI-Driven Drug Repurposing for Rare Diseases
8.2 Capstone Project 2- AI-Powered Patient Stratification for Adaptive Clinical Trials Using a Clinical Trials Simulator GPT
8.3 Capstone Project 3 – Predictive Pharmacovigilance Using Machine Learning

Optional Module: AI Agents for Pharma

1.1 What are AI Agents?
1.2 How Does an AI Agent Work in the Pharma Value Chain
1.3 Core Characteristics of AI Agents
1.4 Importance of AI Agents (General + Pharma)
1.5 Significance of AI Agents in Pharma
1.6 Types of AI Agents?
1.7 Applications and Trends in Pharma
1.8 Case Study: Accelerated Lead Optimization with a Generative AI Agent

Prerequisites

Requires basic biology knowledge, familiarity with pharmaceutical development and regulatory fundamentals, foundational understanding of AI and machine learning, essential data analytics skills, and strong awareness of ethical considerations in AI-powered healthcare.