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 to Predict Thermodynamic Parameters
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.
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