Meet Inspiring Speakers and Experts at our 3000+ Global Events with over 1000+ Conferences, 1000+ Symposiums and 1000+ Workshops on Medical, Pharma, Engineering, Science, Technology and Business.

Explore and learn more about Conference Series : World’s leading Event Organizer

Conference Series Conferences gaining more Readers and Visitors

Conference Series Web Metrics at a Glance

  • 3000+ Global Events
  • 100 Million+ Visitors
  • 75000+ Unique visitors per conference
  • 100000+ Page views for every individual conference

Unique Opportunity! Online visibility to the Speakers and Experts

Renowned Speakers

Barry A. Bunin

Barry A. Bunin

Collaborative Drug Discovery USA

Mark Lautens

Mark Lautens

University Of Toronto Canada

Chistopher J Rhodes

Chistopher J Rhodes

Fresh Lands Environmental Actions UK

Shira Engelberg

Shira Engelberg

Israel Institute of Technology Israel

Mark McLaughlin

Mark McLaughlin

Merck Sharp & Dohme (MSD) Dept. of Process Research and Development USA

Fatih Sirindil

Fatih Sirindil

University of Strasbourg France

Amira Deia Younes

Amira Deia Younes

Associate Director UAE

Sara Torgal

Sara Torgal

Senior Manager Swaziland

Euro MedChem and CADD 2025

Welcome message

 
We are delighted to welcome you to the 4th World Congress on Medicinal Chemistry and Computer Aided Drug Design, taking place on November 25–26, 2025 in Paris, France. This prestigious gathering brings together a global community of researchers, scientists, academics, and industry professionals to share the latest advancements in medicinal chemistry and the innovative applications of computational tools in drug design. The congress will feature cutting-edge presentations, insightful discussions, and valuable networking opportunities, all aimed at advancing research and collaboration in the field. Join us in the vibrant city of Paris for an inspiring and enriching experience as we collectively explore new frontiers in modern drug discovery and development.

 

About Conference


November 25-26, 2025 | Paris, France
The 4th World Congress on Medicinal Chemistry and Computer Aided Drug Design, taking place on November 25–26, 2025 in Paris, is a global platform focused on cutting-edge advancements in drug discovery and computational chemistry. It brings together scientists, researchers, and industry leaders to share innovations in structure-based drug design, AI-driven development, and molecular modeling. The event features expert keynotes, research presentations, and networking opportunities aimed at translating research into real-world pharmaceutical solutions. Held in the vibrant city of Paris, the congress offers both scientific depth and cultural experience.
 
Theme: "Innovations in Molecular Design: Bridging Chemistry and Computation for Next-Gen Drug Discovery"
 
The theme "Innovations in Molecular Design: Bridging Chemistry and Computation for Next-Gen Drug Discovery" emphasizes the transformative fusion of medicinal chemistry with advanced computational tools, which is reshaping the landscape of drug development. By integrating technologies such as molecular modeling, artificial intelligence, machine learning, and bioinformatics with traditional chemical synthesis and analysis, researchers are now able to design more precise, effective, and safer drug candidates at a faster pace and lower cost.
Conference highlights:
 
  • Structure-Based Drug Design (SBDD) and Molecular Docking
  • AI and Machine Learning in Drug Discovery
  • Pharmacokinetics and Pharmacodynamics (PK/PD) Modeling
  • Quantitative Structure-Activity Relationship (QSAR) and ADMET Prediction
  • Peptide and Protein-Based Drug Design
  • Fragment-Based Drug Discovery (FBDD)
  • In Silico Screening and Virtual High-Throughput Screening
  • Medicinal Chemistry of Natural Products and Bioactive Compounds
  • Cheminformatics and Big Data in Medicinal Chemistry
  • Molecular Dynamics and Simulation Techniques

 

Why to Attend?

Attending the 4th World Congress on Medicinal Chemistry and Computer Aided Drug Design is a valuable opportunity for researchers, scientists, and industry professionals to engage with the latest advancements in drug discovery and computational chemistry. The conference offers a platform to learn from leading experts, present innovative research, and build collaborations that can drive future breakthroughs. As the pharmaceutical industry rapidly evolves with the integration of artificial intelligence, machine learning, and molecular modeling, this congress serves as a catalyst for accelerating smarter, more efficient, and targeted drug development. Looking ahead, the event aims to shape the future of therapeutic innovation by promoting interdisciplinary approaches and fostering global partnerships that can address complex medical challenges.
Benefits of attending:
Cutting-edge Insights
Networking Opportunities
Access to Expert Speakers
Innovative Solutions
Professional Development
Collaborative Environment
Global Perspective
Get your abstracts published with unique DOI in International Journals
Get up to 50% discount for publishing your entire article in our open access International Journals
Target Audience:
The 4th World Congress on Medicinal Chemistry and Computer Aided Drug Design is designed to attract a diverse group of professionals, researchers, and industry leaders from the fields of pharmaceutical sciences, chemistry, and computational biology. Attendees will benefit from the opportunity to explore the latest advancements, exchange innovative ideas, and collaborate on strategies that accelerate drug discovery and development.
Key participants include:
Medicinal Chemists
Computational Chemists
Pharmaceutical Scientists
Drug Discovery Researchers
Structural Biologists
Bioinformaticians
Pharmacologists and Toxicologists
Synthetic and Organic Chemists
Cheminformatics Experts
Molecular Modelers and Docking Specialists
Clinical Researchers
Formulation Scientists
R&D Professionals from Pharma and Biotech Industries
University Professors, Postdocs, and Graduate Students
Regulatory Affairs and FDA Representatives
CROs and CMOs
AI and Machine Learning Specialists in Drug Design
Startups and Entrepreneurs in Drug Development
Healthcare Data Scientists
Venture Capitalists and Investors in Biopharma

Scientific sessions /tracks

Advances in Medicinal Chemistry: From Bench to Bedside focuses on the innovative strategies and methodologies driving the discovery and development of new therapeutics. This session highlights the critical role of medicinal chemistry in transforming early-stage compounds into clinically viable drug candidates. Topics include lead identification, scaffold optimization, and structure-activity relationship (SAR) studies aimed at improving potency, selectivity, and pharmacokinetic properties. The session also explores the integration of synthetic chemistry with modern tools like computational modeling, green chemistry approaches, and translational research. By showcasing successful case studies and addressing challenges such as metabolic stability and bioavailability, this session provides a comprehensive view of how medicinal chemistry bridges the gap between laboratory research and real-world therapeutic applications.
Lead compound discovery and optimization
Innovative synthetic strategies for drug-like molecules
Targeted covalent inhibitors and PROTACs
Bridging in vitro efficacy with in vivo performance
Medicinal chemistry contributions to orphan and rare disease drugs
 
Structure-Based Drug Design and Molecular Docking is a cornerstone session in modern drug discovery that focuses on the use of three-dimensional structural information of biological targets to design and optimize drug candidates. This approach leverages crystallographic, cryo-EM, or NMR-derived protein structures to guide the identification of small molecules that can interact specifically and effectively with target sites. Molecular docking plays a key role by predicting the preferred orientation and binding affinity of these molecules within the active site of the target. This session delves into the latest advances in docking algorithms, scoring functions, and validation techniques, as well as their applications in hit identification, lead optimization, and virtual screening. Case studies illustrating the successful application of structure-based methods in designing inhibitors for kinases, GPCRs, and viral enzymes will be featured. Emphasis will also be placed on challenges such as protein flexibility, water-mediated interactions, and the integration of molecular dynamics simulations for more accurate predictions.
Recent Advances in Molecular Docking Algorithms
Scoring Functions: Accuracy, Challenges, and Improvements
Structure-Guided Drug Design Using X-ray, NMR, and Cryo-EM Data
Virtual Screening for Hit Identification and Lead Optimization
 
AI & Machine Learning in Drug Discovery focuses on the integration of advanced algorithms to accelerate and optimize the drug development process. This session highlights how AI models aid in target prediction, virtual screening, compound generation, and ADMET profiling. It also explores deep learning, generative models, and data-driven approaches that improve decision-making in medicinal chemistry. Real-world case studies and challenges like data quality and model interpretability will be discussed.
Deep learning models for compound property prediction
De novo molecular generation using AI
Predictive analytics for toxicity and efficacy
 
Quantum Chemistry and Molecular Simulations explores how quantum mechanical methods and atomistic simulations are applied to understand and predict molecular behavior in drug discovery. This session highlights techniques such as Density Functional Theory (DFT), QM/MM approaches, and molecular dynamics simulations to study reaction mechanisms, binding affinities, and electronic properties. It emphasizes the role of simulations in refining lead compounds, modeling protein-ligand interactions, and predicting molecular stability. Discussions will also cover the integration of these methods with AI and high-performance computing to enhance accuracy and efficiency in drug design.
QM/MM hybrid approaches in drug design
Free energy calculations for ligand optimization
Molecular dynamics for binding affinity estimation
 
Fragment-Based and Ligand-Based Design focuses on two powerful strategies used to identify and optimize drug candidates. Fragment-based design involves screening low-molecular-weight chemical fragments that bind weakly to a target and then growing or linking them to create potent inhibitors. Ligand-based design, on the other hand, relies on knowledge of known active compounds to build predictive models such as QSAR and pharmacophores. This session covers methods for fragment screening, hit optimization, and ligand-based virtual screening, highlighting how both approaches complement each other in accelerating lead discovery and improving drug-like properties.
Virtual screening of fragment libraries
Pharmacophore modeling and 3D-QSAR techniques
Scaffold hopping and bioisosteric replacements
 
Computational Drug Discovery and Design focuses on the use of in silico methods to accelerate and refine the process of developing new therapeutics. This session covers key techniques such as molecular docking, pharmacophore modeling, QSAR, molecular dynamics simulations, and virtual screening. By integrating structural data, cheminformatics, and predictive algorithms, computational approaches help identify promising compounds, optimize leads, and reduce experimental costs. The session also explores how these tools are applied in real-world case studies to enhance decision-making in early-stage drug discovery.
In silico screening and molecular docking techniques
Structure-activity relationship (SAR) and QSAR modeling
Free energy calculations and molecular dynamics simulations
 
Cheminformatics and Big Data in Drug Design highlights the critical role of data-driven approaches in modern pharmaceutical research. This session focuses on the use of cheminformatics tools to manage, analyze, and visualize vast chemical and biological datasets for informed decision-making in drug discovery. Topics include molecular descriptor analysis, compound library design, similarity searching, and data mining techniques. The integration of big data analytics with AI and machine learning enables prediction of drug properties, identification of novel targets, and acceleration of lead optimization. Real-world applications and challenges in data quality, standardization, and interoperability will also be discussed.
Data mining in compound libraries
Chemical space navigation and visualization
Integration of multi-omics datasets
 
Computational Approaches for Target Identification and Validation explores how in silico tools are revolutionizing the early stages of drug discovery by uncovering and confirming viable biological targets. This session covers methods such as network pharmacology, systems biology modeling, reverse docking, and machine learning-based target prediction. These approaches help identify disease-relevant proteins, predict drug-target interactions, and assess target druggability with greater speed and accuracy. Emphasis is placed on integrating multi-omics data, pathway analysis, and virtual screening to streamline validation processes and reduce experimental costs.
Network pharmacology and systems biology
In silico off-target prediction
Multi-target drug design
 
Innovations in Molecular Visualization and Virtual Reality Tools focuses on the cutting-edge technologies that enhance how researchers interact with and understand molecular structures. This session highlights advancements in 3D visualization platforms, interactive modeling, and virtual reality (VR) environments that allow immersive exploration of protein-ligand interactions, binding sites, and conformational changes. These tools improve the accuracy of molecular design, foster intuitive understanding of complex biological systems, and support collaborative drug discovery efforts. Applications in education, real-time docking analysis, and structure-based design will also be discussed.
Immersive molecular modeling environments
3D visualization for structure-guided design
HCI (Human-Computer Interaction) in medicinal chemistry
 
Peptide and Macrocycle Drug Design explores the growing field of designing therapeutics based on peptides and cyclic molecules, which offer high specificity and affinity for challenging biological targets. This session highlights strategies for improving the stability, permeability, and bioavailability of peptide-based drugs, as well as computational methods for modeling their complex structures. Topics include macrocyclization techniques, structure-activity relationships, and the design of constrained peptides for targeting protein–protein interactions. Advances in synthetic approaches and delivery systems will also be discussed, showcasing the therapeutic potential of these versatile molecules.
Computational strategies for peptide optimization
Cyclic peptide modeling and docking
Challenges in cell permeability and stability
 
In Silico ADME-Tox Prediction and Optimization focuses on computational methods used to evaluate the Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADME-Tox) profiles of drug candidates early in the discovery process. This session highlights tools and models that predict pharmacokinetic behavior, potential toxicity, and safety risks, helping to minimize late-stage failures. Topics include QSAR models, machine learning-based toxicity predictors, and virtual screening filters for drug-likeness. By integrating these in silico approaches, researchers can optimize compound properties more efficiently, reduce animal testing, and accelerate the development of safer, more effective drugs.
Tools and models for predicting pharmacokinetics
Early detection of toxicity through simulations
Integration into early-stage drug development
 
Cloud Computing and Open Science Platforms in CADD explores how cloud-based technologies and collaborative platforms are transforming Computer-Aided Drug Design (CADD). This session highlights the use of scalable computing resources for high-throughput virtual screening, molecular simulations, and AI-driven modeling. It also emphasizes the role of open-access databases, shared tools, and community-driven initiatives in accelerating innovation and enhancing reproducibility. Topics include cloud-enabled molecular docking, data sharing standards, and collaborative research environments that break down barriers between academia, industry, and global research communities.
Collaborative platforms for molecular design
High-throughput screening in the cloud
Data sharing and reproducibility challenges
 
Synthetic and Green Medicinal Chemistry focuses on innovative and sustainable approaches to the design and synthesis of drug molecules. This session highlights advances in synthetic methodologies that improve efficiency, selectivity, and scalability while minimizing environmental impact. Topics include eco-friendly reaction conditions, solvent-free processes, biocatalysis, and the use of renewable feedstocks. Emphasis is placed on integrating green chemistry principles into medicinal chemistry workflows to reduce waste, enhance safety, and support sustainable pharmaceutical development without compromising therapeutic effectiveness.
Eco-friendly synthesis of drug candidates
Biocatalysis in pharmaceutical chemistry
Late-stage functionalization techniques
 
Target Identification and Validation is a critical phase in the drug discovery process that focuses on recognizing and confirming biological molecules—such as proteins, genes, or pathways—that are directly involved in disease progression. This session explores both experimental and computational strategies for identifying potential drug targets and validating their relevance and drug ability. Topics include genomics and proteomics approaches, CRISPR-based validation, RNA interference, bioinformatics tools, and disease pathway analysis. Emphasis is placed on ensuring that selected targets are not only biologically significant but also therapeutically actionable, thereby reducing the risk of failure in later drug development stages.
Computational approaches for target prediction
Network-based drug-target interaction studies
Drug repurposing and repositioning strategies
 
Neuropharmacology and CNS Drug Design focuses on the discovery and development of therapeutics targeting the central nervous system (CNS), addressing complex neurological and psychiatric disorders. This session highlights the challenges of designing drugs that can cross the blood-brain barrier, maintain CNS selectivity, and minimize neurotoxicity. Topics include neuroreceptor targeting, modulation of neurotransmitter systems, computational CNS drug modeling, and strategies to improve brain bioavailability. Emphasis is placed on innovative approaches for treating conditions such as Alzheimer’s, Parkinson’s, depression, and epilepsy, with insights into both small molecules and biologics in CNS therapeutics.
Blood-brain barrier modeling and prediction
Design of CNS-active ligands
CNS toxicity profiling through computational tools
 
Peptide and Nucleic Acid Therapeutics focuses on the design and development of biologically inspired drugs that target diseases at the molecular level with high specificity. This session explores the therapeutic potential of peptides, antisense oligonucleotides, siRNA, mRNA, and aptamers in treating a wide range of conditions, including genetic disorders, cancer, and infectious diseases. Key topics include strategies to enhance stability, delivery systems to improve cellular uptake, and chemical modifications to boost efficacy and reduce immunogenicity. Advances in synthesis, formulation, and regulatory considerations will also be discussed, highlighting the growing role of these molecules in next-generation therapeutics.
Design and modification of therapeutic peptides
RNA-targeted drug design and antisense strategies
Delivery systems and formulation innovations
 
Case Studies in Drug Discovery and Development provides real-world insights into the journey of transforming a scientific idea into an approved therapeutic. This session showcases detailed examples of successful drug discovery projects, highlighting key decision points, challenges encountered, and strategies that led to breakthrough outcomes. Topics include target selection, lead optimization, preclinical testing, clinical trial design, and regulatory navigation. By analyzing both successes and failures, participants gain a deeper understanding of the multidisciplinary efforts, timelines, and innovations required to bring effective and safe drugs to market.
Success stories in medicinal chemistry and CADD
Failures and lessons learned in lead optimization
Industry-academia collaboration models
 
Molecular Dynamics and Free Energy Calculations focus on simulating the physical movements of atoms and molecules over time to gain insights into biological processes and drug-target interactions at the atomic level. This session explores how molecular dynamics (MD) helps predict conformational changes, binding modes, and stability of protein-ligand complexes. Free energy calculations, including MM-PBSA, FEP, and thermodynamic integration, are highlighted for their role in accurately estimating binding affinities and guiding lead optimization. Emphasis is placed on the integration of these techniques with experimental data and their application in rational drug design, helping researchers better understand molecular behavior in dynamic biological environments.
Principles and Applications of Molecular Dynamics (MD) Simulations
Force Fields and Parameterization in MD
Conformational Sampling and Protein Flexibility Analysis
 
Ligand-Based Drug Design and Virtual Screening focuses on using information from known bioactive compounds to identify and design new drug candidates without requiring the target’s 3D structure. This session highlights key techniques such as Quantitative Structure-Activity Relationship (QSAR) modeling, pharmacophore generation, and molecular similarity analysis to predict the activity of novel molecules. Virtual screening of large compound libraries based on ligand features enables rapid hit identification and prioritization. Emphasis is placed on the integration of machine learning, cheminformatics tools, and experimental data to enhance accuracy and reduce false positives in the drug discovery pipeline.
Principles of Ligand-Based Drug Design (LBDD)
Pharmacophore Modeling and 3D Alignment Techniques
Quantitative Structure-Activity Relationship (QSAR) Models
 
Modern Strategies in Lead Identification and Optimization focuses on innovative approaches used to discover and refine chemical compounds with therapeutic potential. This session explores how advances in high-throughput screening, fragment-based drug discovery, and computational modeling have accelerated the identification of initial hits. It also delves into lead optimization techniques such as structure-activity relationship (SAR) analysis, bio isosteric replacement, and property-based design to enhance potency, selectivity, and drug-like properties. Emphasis is placed on integrating multidisciplinary tools, including AI, structural biology, and cheminformatics, to streamline the path from hit to high-quality clinical candidate.
High-Throughput and Fragment-Based Screening Techniques
Structure-Activity Relationship (SAR) and Lead Refinement
Bioisosterism and Scaffold Hopping in Lead Optimization

Participation presentation option

At the 4th World Congress on Medicinal Chemistry and Computer Aided Drug Design, we offer diverse participation formats to engage professionals from academia, pharmaceutical industries, research institutions, and biotech startups. Whether you’re a leading researcher, an early-career scientist, or a professional seeking to explore innovations in drug discovery, there’s a role for everyone in this global forum.
 
Oral Presentations: Present your latest research through 25–30 minute talks within focused scientific sessions. Oral presenters will engage with a global audience of experts, receive feedback, and spark collaborative discussions on medicinal chemistry, molecular modeling, or AI-based drug design.
 
Poster Presentations: Showcase your work in a dynamic and interactive format during our poster sessions. Ideal for presenting experimental studies, novel compounds, or in silico models in drug discovery, these sessions allow for direct, personalized discussions with peers and industry leaders.
 
Workshops: Participate in hands-on, skills-based workshops led by specialists in cheminformatics, pharmacokinetics, QSAR modeling, and structure-based drug design. These sessions are designed to provide practical tools and cutting-edge insights for accelerating drug development.
 
Panel Discussions: Engage with thought leaders from academia, pharma, and regulatory sectors in interactive panels. Topics will cover emerging challenges and future directions in medicinal chemistry, computational drug development, regulatory trends, and AI integration in therapeutics.
 
Exhibitor Opportunities: Showcase your company’s products, technologies, software, or services in our dedicated exhibition space. A prime opportunity for CROs, biotech firms, and tool developers to connect with researchers, decision-makers, and potential partners.
 
Virtual Participation: Unable to travel to Paris? Join us virtually with full access to live-streamed presentations, interactive Q&A sessions, and online networking lounges. Engage from anywhere while staying connected to the latest in medicinal and computational chemistry.
 
Delegate Participation: Not presenting? Register as a delegate to access all scientific sessions, workshops, and networking activities. Perfect for those seeking to expand their knowledge, form partnerships, and stay at the cutting edge of drug discovery and development.
 
To know more about exhibitor booth details and benefits visit WHY TO EXHIBIT WITH US?
Send your queries to contact@europeanmeets.com
 
Advertisement: The conference program is a valuable resource that all attendees refer again and again as they navigate the conference. Advertising in the conference program is a great way to market and can help you secure long term business.
Send your proposal to contact@europeanmeets.com to know the available advertisement options and prices
             Sponsor Euro MedChem and CADD 2025
             Premium Sponsorship package
            Additional Sponsorship package
Mail the program manager at berryaimee309@gmail.com or WhatsApp on (+44-2045861247 )to know more about the sponsorship packages.
'Once again it is an honor to welcome you all to the upcoming “4th World Congress on Medicinal Chemistry and Computer Aided Drug Design” scheduled on November 25-26, 2025 Paris, France’

 

To Collaborate Scientific Professionals around the World

Conference Date November 25-26, 2025

For Sponsors & Exhibitors

sponsor@conferenceseries.com

Speaker Opportunity

Past Conference Report

Supported By

Journal of Drug Metabolism & Toxicology Clinical & Medical Biochemistry Medicinal Chemistry

All accepted abstracts will be published in respective Conference Series International Journals.

Abstracts will be provided with Digital Object Identifier by


Media partners & Collaborators & Sponsors

mediapartner

Media Partner

mediapartner

Media Partner

mediapartner

Media Partner

mediapartner

Media Partner

mediapartner

Media Partner

mediapartner

Media Partner

mediapartner

Media Partner

Keytopics

  • 3D-QSAR Techniques
  • ADMET (Absorption, Distribution, Metabolism, Excretion, Toxicity) Profiling
  • Allosteric Modulators In Drug Discovery
  • Anticancer Drug Design
  • Antimicrobial Drug Discovery
  • Bioisosterism And Scaffold Hopping
  • CADD For Rare And Neglected Diseases
  • Case Studies And Success Stories In CADD
  • Challenges And Limitations In CADD
  • Chiral Drugs And Stereochemistry In Medicinal Chemistry
  • Cloud Computing And Big Data In Drug Discovery
  • CNS Drug Design And Neuropharmacology
  • Combinatorial Chemistry Approaches
  • Computational Approaches For RNA-Targeted Drug Discovery
  • Computational Methods For Protein-Protein Interaction Inhibitors
  • Computational Toxicology
  • Data Mining And Chemoinformatics
  • De Novo Drug Design
  • Deep Learning Applications In Medicinal Chemistry
  • Drug Discovery And Development Process
  • Drug Metabolism And Toxicity Prediction
  • Drug Repurposing And Repositioning
  • Fragment Growing And Linking Techniques
  • Fragment-Based CADD
  • Fragment-Based Drug Discovery
  • High-Throughput Screening In Drug Discovery
  • Homology Modeling Of Drug Targets
  • In Silico ADMET Prediction
  • Integration Of CADD With Experimental Methods
  • Lead Hopping Techniques
  • Ligand-Based Drug Design (LBDD)
  • Machine Learning And AI In Drug Design
  • Medicinal Chemistry Of Natural Products
  • Molecular Descriptor Calculation And Analysis
  • Molecular Docking Algorithms And Scoring Functions
  • Molecular Docking And Virtual Screening
  • Molecular Dynamics And Free Energy Calculations
  • Molecular Dynamics Simulations In Drug Design
  • Multi-Scale Modeling Approaches
  • Patent Strategies In Medicinal Chemistry
  • Peptide And Protein-Based Therapeutics
  • Pharmacokinetics And Pharmacodynamics In Drug Design
  • Pharmacophore Modeling
  • Polypharmacology And Multi-Target Drug Design
  • Predictive Models For Drug-Drug Interactions
  • Prodrug Design And Development
  • Protein-Ligand Interaction Analysis
  • Quantitative Structure-Activity Relationship (QSAR)
  • Quantum Mechanics/Molecular Mechanics (QM/MM) In Drug Design
  • Role Of CADD In Natural Product Drug Discovery
  • Role Of Computational Chemistry In Medicinal Chemistry
  • Simulation Of Drug Resistance Mechanisms
  • Software Tools For CADD
  • Structure-Based Drug Design (SBDD)
  • Structure-Based Virtual Screening
  • Synthesis Of Novel Therapeutic Agents
  • Targeted Drug Delivery Systems
  • Virtual Screening Methods And Applications
  • Visualization Techniques In CADD
  • Modern Strategies In Lead Identification And Optimization