The biomedical sector is undergoing a substantial and challenging change. Whole genome sequencing has opened up the field of genome-scale biology and has established a trend towards larger-scale experiments. Small-scale biology has also benefited from a wealth of new data. Easy access to this data often eliminates months of traditional lab time. Whether operating on a large or small scale, the use of mathematical algorithms and simulation is becoming an integral part of biological research.
pSeven is a software platform for data analysis and optimization, that uses a complete toolkit of innovative and advanced algorithms to quickly and efficiently identify the best solution when the experiment has many important factors and several conflicting goals. When a model of the system under investigation is not available, pSeven can generate an approximation model based on empirical and experimental data, so new options can be explored.
pSeven brings well-established engineering data analysis and optimization technologies to the biotech and pharmaceutical industries, making the process predictable and repeatable. It covers a wide variety of applications, including drug design, implants development, skin care products enhancement etc.
Surrogate modeling techniques allowed to speed up the prediction of thermodynamic parameters of organic molecules many-fold and to obtain better prediction quality compared to common methods employed in computational chemistry.