Medicinal Chemistry

  1. Optimization of Drug-Like Properties
    1. Lipophilicity
      1. Importance of lipophilicity in drug design
        1. Impact on absorption and distribution
          1. Influence on blood-brain barrier penetration
          2. Measurement and prediction methods
            1. Log P and log D values
              1. Chromatographic methods
                1. Computational estimation
                2. Strategies to optimize lipophilicity
                  1. Structural modifications
                    1. Prodrug approaches
                      1. Use of lipophilic/hydrophilic balance (LHB) concepts
                    2. Solubility
                      1. Impact of solubility on bioavailability
                        1. Relation to dissolution rate
                          1. Role in oral drug delivery
                          2. Solubility prediction and measurement
                            1. Solubility testing techniques
                              1. Prediction models and software tools
                              2. Methods to enhance solubility
                                1. Salt formation
                                  1. Use of cosolvents and surfactants
                                    1. Nano-formulation techniques
                                      1. Solid dispersion methods
                                    2. Permeability
                                      1. Role in drug absorption and distribution
                                        1. Impact on oral and transdermal delivery
                                          1. Influence on central nervous system access
                                          2. Assessment techniques for permeability
                                            1. Caco-2 cell assays
                                              1. Parallel artificial membrane permeability assays (PAMPA)
                                              2. Approaches to improve permeability
                                                1. Use of permeability enhancers
                                                  1. Chemical modifications
                                                    1. Lipid-based delivery systems
                                                  2. Metabolic Stability
                                                    1. Importance in drug development
                                                      1. Impact on drug half-life and clearance
                                                        1. Role in species-specific metabolism
                                                        2. Methods for studying metabolic stability
                                                          1. In vitro liver microsomes and hepatocytes assays
                                                            1. In vivo metabolic studies
                                                            2. Strategies to enhance metabolic stability
                                                              1. Structural modification to resist metabolic breakdown
                                                                1. Use of bioisosteres
                                                                  1. Incorporation of metabolically stable linkers
                                                                2. Additional Properties Influencing Drug-Likeness
                                                                  1. Topological polar surface area (TPSA)
                                                                    1. Relation to absorption and permeability
                                                                    2. Hydrogen bonding potential
                                                                      1. Effects on solubility and permeability
                                                                      2. Molecular weight considerations
                                                                        1. Impact on absorption and biological activity
                                                                      3. Optimization Techniques
                                                                        1. Lead compound modification
                                                                          1. Iterative testing and refinement
                                                                            1. Use of structure-activity relationship (SAR) data
                                                                            2. Computer-aided optimization
                                                                              1. Machine learning models
                                                                                1. Quantitative structure-property relationship (QSPR)
                                                                                2. High-throughput screening and library design
                                                                                3. Challenges and Balancing Factors
                                                                                  1. Trade-offs between solubility, permeability, and metabolic stability
                                                                                    1. Balancing potency, efficacy, and drug-likeness
                                                                                      1. Bridging preclinical and clinical optimization
                                                                                      2. Case Studies and Practical Applications
                                                                                        1. Analysis of successful optimization strategies in marketed drugs
                                                                                          1. Lessons learned from failed drug candidates
                                                                                          2. Future Directions in Optimization
                                                                                            1. Integration of novel analytical methods
                                                                                              1. Use of advanced computational models
                                                                                                1. Incorporation of holistic approaches for multi-parameter optimization