Despite advanced developments in molecular testing of disease, antibodies, as biomarkers, play an important role in diagnosing disease, checking immune response and for serological surveillance. There is an increasingly urgent need for rapidly adaptable, sensitive, low-cost antibody diagnostics not only for existing diseases but also for the proper case management and control of emerging and re-emerging infectious diseases, particularly in resource constrained settings. Peptide based diagnostics are a potential alternative to tests that involve recombinant protein antigens, which, while generally effective, have constraints with respect to reproducibility and adaptability. Kode technology is a highly adaptable platform that uses function-spacer-lipid (FSL) constructs to attach epitopes to cells (kodecytes) for use in diagnostic assays. The feasibility of designing more refined synthetic antigens (short peptide epitopes) provides potential for enhanced sensitivity and specificity. Kodecytes can be implemented easily into a simple, rapid, sensitive and relatively less expensive diagnostic using the Kode technology platform. One objective of this study was to develop an algorithm for designing FSL peptide constructs using bioinformatics. This research initially selected two different complex pathogens (T. pallidum and Leptospira) to develop an algorithm and develop Kode technology antibody diagnostics compatible with existing routine serologic platforms. However, with the unprecedented appearance of the COVID-19 (SARS CoV-2) pandemic, this research was extended to create a potential antibody diagnostic assay for COVID-19. Candidate peptides were made for T. pallidum, Leptospira and SARS CoV-2 using the peptide identification and FSL peptide selection algorithm. Validation and the functional prediction of candidate peptides were performed using blood samples and the kodecyte assay. Among the candidate peptides, T. pallidum and SARS CoV-2 had one potential candidate peptide suitable for diagnostics. Assessing the datasets over time will help in further refining the algorithm. The syphilis kodecyte assay and COVID-19 kodecyte assay achieved specificity and sensitivity at least equivalent to an established EIA antibody diagnostic. The Leptospira kodecyte assay was more challenging to validate, as there was minimal access to samples, but the preliminary results were good, and while most of the candidate peptides worked, further validation is required. This research built successful kodecyte assays for three diseases. Kodecyte assays described in this thesis are β versions and will ultimately need to undergo regulatory approval processes and product development trials to be able to be implemented in clinical use. However, despite not yet being optimized, the assays reported are functional and usable.