To provide students with a foundation for the further study of mathematics and statistics and give them an adequate mathematical basis for the study of related disciples with regard to pharmaceutical industry.
Scientific notation, powers and logs: Exponential functions and natural logs, Equations with one or two unknown powers to Reduction of non-linear equations to linear forms. Examples pharmaceutical shelf-life estimation.
Unit conversion, ppm, molecular mass calculations, dilutions and molarity(titration examples, dissociation of weak base/acid (Ka, Kb, etc), solubility).
Fitting a line to linear data (calibration curves – Absorbance versus Concentration-Estimation Unknown).
Statistics: Basic concepts of central tendency and spread such as the Mean, Mode, Median, Standard Deviation, Range with reference to ISO-3534 and ISO-5725 (Accuracy –Trueness and Precision). Probability: Simple probability and combinations (with application to quality control), Mutually exclusive and independent events. Sensory Analysis examples.
Linear Programming: Reviewing inequalities and simultaneous equations. Optimizing profits and minimizing cost with respect to linear constraints. Applications of linear programming with regard to ingredient blending for pharmaceutical products.
Differentiation and Integration: Identifying of maxima, minima and inflexions. Introduction to partial differential equations. Definite and Indefinite Integrals, Area under a curve (AUC).
Formal lectures will be used to introduce topics, and apply techniques. The assessment includes 2 online MCQ assessments that are aligned to the key learning outcomes identified as important to underpin the wider Programme curriculum and which must be passed at 70%. These can be repeated throughout the module duration until successfully passed, and feedback will be provided.
|Module Content & Assessment