Systems Pharmacology


Figure 1


Schematic representation of therapeutic drug effect on individual homeostasis. In the


one drug-one target model the health of an individual was


determined, in many cases, by a single diagnostic indicator


such as blood glucose levels in diabetic patients. A patient was determined to be healthy if


the diagnostic value was within a range limit (Healthy – black line represents the range). As


disease onset and progression occurred the individual’s body was determined to be out of homeostasis (Diseased).


However, disease severity was still determined by one


diagnostic marker. Application of a therapeutic drug, which theoretically only interacted with a single target, should


move the individual back into homeostasis. If the drug


interacted with an ‘off-target’ then the condition of the patient could deteriorate


(Adverse). In the case of a one drug-multi-target-


pathway/network drug of


systems pharmacology, the fundamental homeostatic model still applies, however


instead of a one-dimensional diagnostic range and limited


efficacy effect, there is a more comprehensive data rich definition of a homeostatic


‘circle’ Such an approach leads to a more efficacious


treatment and minimisation of toxicity, safety and side-effects


diagnosed with the same disease indication respond differently to the same therapeutic drug10. For example, Spears and co-workers analysed the effectiveness of a number of different drug classes against major disease indications11. They found that most drugs were ~30-75% effective as deter- mined by patient responses. The lowest responders were oncology patients treated with conventional cancer chemotherapy agents (25% of patients responded positively). In contrast, the highest per- centage of patient responders resulted from treat- ment with Cox-2-inhibitors (80%). Therapeutic drugs were reported to be ineffective for Alzheimer’s (70%), arthritis (50%), diabetes (43%) and asthma (40%) patients11.


We have argued in the past that the ‘Blockbuster


Model’ has inadvertently led to the ‘wagon-of- woe’ for the DDD process12. This approach utilised the ‘one drug-one target’ model that was relatively effective in large, poorly-defined, hetero- geneous patient populations. We have suggested the integrated use of more efficient technologies13, decision-making tools13, systems biology14,15 and personalised/precision medicine16-18 in order to overcome the limitations of such a model. We have presented the concept of systems biology-person- alised/precision medicine approaches for the pro- duction of more effective and safe therapeutic


34


drugs17, particularly in the treatment of Alzheimer’s disease19. In addition, we have sug- gested that the development of precision medicine drugs2, as well as an integrated technology plat- form-DDD approach3may also facilitate improved drug pipeline products. In this manuscript we dis- cuss drug polypharmacology, which has usually been equated with therapeutic drug-target promis- cuity, resulting in safety/toxicological side-effects and reduced efficacy20,21. More recently, the term has been used to describe the benefits of a single drug affecting change at multiple targets (one drug- multi-targets) for more efficacious impact of the drug predicated on systems biology and precision medicine considerations22. All this is considered and discussed as well as the emerging paradigm of systems pharmacology23.


Human complexity, systems biology and precision medicine The original ‘one-drug-one target’ model was predicated on a rather simplistic perspective of human anatomy and physiology. The health of an individual was determined by a number of diag- nostic markers such as blood glucose levels. When the concentration levels of such a marker changed beyond a certain defined clinical range then the patient was diagnosed with a specific disease indi- cation (see Figure 1 for a schematic representation


Drug Discovery World Winter 2018/19


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