Genomic profiling has shown that not all cancer patients who share similar macro- and microscopical features harbour the same underlying molecular mechanism. This suggests the urge for matching patients to mechanism-based cancer therapies, independent of their primary tumour location and histology (Bashraheel et al. 2020). Currently, precision oncology trials provide personalised treatments based on the druggable variants found in a patient genetic makeup. Typically, those trials target single genetic variants (Schmidt et al. 2016; Murciano-Goroff et al. 2020) or provide combination therapies targeting single, mechanistically unrelated proteins which have been proven to be ineffective and or insufficient (Choobdar et al. 2019; Lazareva et al. 2021). In parallel, these variants are allocated to so-called canonical signalling pathways, e.g., KEGG pathways, Wiki Pathways. However, these are rather curated mind maps only combining similar signalling proteins or messengers. They do not represent true cellular signalling entities. Alternatively, signalling modules can be constructed in an unbiased manner from the interactome using validated seed proteins, also termed cancer driver genes, resulting in fragments and often mixtures of the above curated pathways (Nogales et al. 2022). These modules likely represent the true cancer mechanism and concerted network modulation with multiple mechanistically related drugs all acting on the same module i.e., network pharmacology, promise to be much more effective than targeting single unrelated variants (Cheng et al. 2019). As complex tumours will require multiple drugs targeting several modules (Sanchez-Vega et al. 2018), we start with low complexity tumours with a low mutational burden, e.g., thyroid cancer and diffuse intrinsic pontine gliomas (DIPG) (Vogelstein et al. 2013). Here, we (i) construct de-novo disease modules to identify drug targets and repurposable drugs, (ii) apply diagnostic assays to detect the patient-specific perturbed modules and (iii) decide on the therapeutic strategy to correct the modules using network pharmacology. Repurposable drugs are ranked based on clinical feasibility and other parameters. This allows a fundamentally new approach to cancer therapy often using low-side effect drugs acting in concert to improve patient survival and quality of life by implementing biology-informed drug interventions.