Solubility is a crucial property to optimise in the development of peptides and proteins as therapeutic compounds. Biologics, which are drugs based on biological compounds such as proteins, inherently possess many beneficial properties such as low toxicity and high specificity. Often, however, they exhibit only limited solubility, which makes them unsuitable to be developed into drugs. Screening out molecules of insufficient solubility is a standard step used in drug development. Usually, this step is done in vitro, at a late stage in the process as it is expensive. In silico methods, at least in principle, offer the advantage of reducing the cost of this screening, while simultaneously eliminating unsuitable candidates much earlier in the process. One such method is CamSol [1], a sequence-based solubility predictor developed in the Centre for Misfolding Diseases, to assess and improve the solubility of proteins. The goal of this PhD was to develop a new method, built upon the foundations of CamSol, that predicts the solubility of proteins and peptides containing non-natural amino acids and to incorporate the effects of formulation pH. A particularly exciting aspect of this project concerning the translation into industrial applications, is that it was carried out in collaboration with AstraZeneca. The effects of pH on the solubility of proteins are well understood at least in outline, but there are no sequence-based methods that can reliably predict the solubility of biologics at varying pH values. Similarly, no prediction method is currently capable of assessing the effects of non-natural amino acids on the solubility of proteins. On the experimental side, a high-throughput, low material requirement in vitro method was developed to measure the solubility of proteins and peptides to verify the predictions. Our results show that the correlation between the predicted and measured solubilities is high, confirming that these new capabilities of CamSol are valid tools that can be employed to facilitate drug development.