Atherosclerosis is a pathological condition that needs extensive research beyond clinical studies. This small and very practical book presents bloodstream modeling of low-density lipoprotein (LDL) and high-density lipoprotein (HDL) cholesterol concentrations as key indicators of atherosclerosis.

Text that explains the model takes up only the first few pages. The numerical algorithm used for solving the partial differential equations (PDEs) is the method of lines (MOL), which is a general method for solving PDEs. As a result, the book resembles an article, with a large appendix containing the actual R code. The code is clean--that is, easy to understand and well documented--but neither optimized to run on high-performance architectures nor parallelized. In fact, the focus is on developing the methodology to model atherosclerosis on desktops and computers with limited memory, using common R distributions.

The book could be useful as a methodology guide for researchers and graduate students dealing with the modeling of biological systems. However, because modern desktops use multicore processors, it’s a pity that the proposed code is only sequential. The book has value as a methodology and startup guide for developing models using scripting languages such as R and Python.