for the use of a new treatment or to develop a new treatment methodology. Consid-

ering a typical example in the field of oncology, wherein a biomarker that can

capture overexpression of the growth factor protein HER-2, known to be transmit-

ting growth signals to breast cancer cells, could be a potential predictive biomarker

to provide treatment for breast cancer patients by using a biosimilar such as

trastuzumab (Herceptin), by blocking the effects of HER-2 receptors. While, prog-

nostic biomarkers can be considered as a pretreatment measurement for providing

the accurate information and collecting the research data regarding the long-term

expected results in case of untreated patients and those receiving the standard

treatment (Matsui 2013).

To combat the burden of disease like cancer and achieve improved treatment

outcomes, modern oncology is also shifting from empirical treatment strategies to

biomarker-based treatment models based upon the molecular profile of the tumour.

The novel biomarkers, like circulating tumour cells (CTCs) and/or circulating

fragments of tumour DNA (ctDNA) present in the blood, can be identified through

liquid biopsy (blood test). This approach holds the promise to guide treatment

selection, facilitate accurate patient risk stratification, predict response and identify

the failure of treatment early, thereby allowing a timely shift of therapeutic strategy

along with new therapeutic development (Payne et al. 2019).

The use of biomarkers during drug discovery is associated with two- to threefold

increase in gaining regulatory approval and less attrition rates. This helps to speed up

the process for getting new medicines for diseases whose treatment is not available

till yet. Ideally, the companies should use biomarker strategy during the initial stages

of drug discovery, but at least, their strategy should include collecting samples

during clinical trials/clinical research. The collected samples during clinical trials/

clinical research again become a valuable tool for biomarker and drug discovery as a

part of reverse translational research. Thus, it is expected that reverse translational

research and integration of novel biomarkers into clinical development would

facilitate new medical product that could promote personalised medicine. In a

currently changing global environment and various new diseases, the world of

biomarkers is considered as good diagnostic companion of an individual as well as

in clinical development. Furthermore, reverse translational research can recognise

novel biomarkers for identifying novel therapeutic targets, expediting rapid devel-

opment of diagnostics and personalised medicines during drug discovery (Fig. 9.3).

Although this seems to have a long way to develop improved drugs that work

optimally in selecting patients with the concept of right patient, right drug and

dose at the right time for a definite outcome in personalised medicine (Shakhnovich

2018).

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