Group 2: Software tools to use pharmacogenetic information for precision medicine in cancer

1. Software that can be used to apply precision medicine to treat cancer.

1.1. Software analysis of Next-Generation Sequencing (NGS) data provides basis for precision medicine in pancreatic cancer.

1.2. Using radiogenomics in precision medicine for breast cancer.

1.3. Whole Genome Sequencing (WGS) approaches for cancer genomics and precision medicine.

2. Companies working on software to facilitate the analysis of tumor mutations that could be targeted with novel treatments

2.1. Perthera manages the process of tumor testing to provide cancer patients and phsycians with ranked therapuetic options.

2.2. Genomenon provides disease-gene-variant relationships from scientific literature for gene and variant interpretation.

2.3. DeepVariant analyzes using a deep neural network to call genetic variants from NGS DNA data.

3. Ideal characteristics in a software tool to help in the identification of good drug-gene mutation pairs

3.1. Data sets and bioinformatics tools to further the discovery of mutation-specific targets (e.g. in acute myeloid leukemia) with an emphasis on web-based applications should be open, accessible, user-friendly, and do not require coding experience to navigate.

3.2. These technologies in the laboratory need the scalability, affordability, and speed to characterize thousands of patients in the clinic for individualized or precision cancer care.

3.3. Many software packages should be powerful and free, and supported by well-known institutions

4. Difficulties of perform data analysis on genomics information from tumors

4.1. Tumors complexity makes the detention of cancer specific copy number variations difficult. Whole Exome Sequencing introduces more biases and noise that make copy number variation detection very challenging.

4.2. Real-time assessment of the tumor sub-clonal architecture remains limited by the high rate of errors produced by most genome-wide sequencing methods as well as the practical difficulties associated with serial tumor genotyping in patients.

4.3. One important problem in cancer genomics or epigenomics research, especially from high-throughput technologies, is that the solid tumor tissues obtained from clinical practice are highly heterogeneous.