The Conflict Between Complex Systems and Reductionism

Abstract

DESCARTES’ REDUCTIONIST PRINCIPLE HAS HAD A PROfound influence on medicine. Similar to repairing a clock in which each broken part is fixed in order, investigators have attempted to discover causal relationships among key components of an individual and to treat those components accordingly. For example, if most of the morbidity in patients with diabetes is caused by high blood glucose levels, then control of those levels should return the system to normal and the patient’s health problems should disappear. However, in one recent study this strategy of more intensive glucose control resulted in increased risk of death. Likewise, chemotherapy often initially reduces tumor size but also produces severe adverse effects leading to other complications, including the promotion of secondary tumors. Most important, little evidence exists that more aggressive chemotherapies prolong life for many patients. In fact, chemotherapies may have overall negative effects for some patients. Most medical treatments make sense based on research of specific molecular pathways, so why do unexpected consequences occur after years of treatment? More simply, does the treatment that addresses a specific disease-related component harm the individual as a whole? To address these questions, the conflict between reductionism and complex systems must be analyzed. With increasing technological capabilities, these systems can be examined in continuously smaller components, from organs to cells, cells to chromosomes, and from chromosomes to genes. Paradoxically, the success of science also leads to blind spots in thinking as scientists become increasingly reductionist and determinist. The expectation is that as the resolution of the analysis increases, so too will the quantity and quality of information. High-resolution studies focusing on the building blocks of a biological system provide specific targets on which molecular cures can be based. While the DNA sequence of the human gene set is known, the functions of these genes are not understood in the context ofadynamicnetworkandtheresultant functional relationship tohumandiseases.Mutations inmanygenesareknowntocontribute to cancers in experimental systems, but the common mutationsthatactuallycausecancercannotyetbedetermined. Many therapies such as antibiotics, pacemakers, blood transfusions, and organ transplantation have worked well using classic approaches. In these cases, interventions were successful in treating a specific part of a complex system without triggering system chaos in many patients. However, even for these relatively safe interventions, unpredictable risk factors still exist. For every intervention that works well there are many others that do not, most of which involve complicated pathways and multiple levels of interaction. Even apparent major successes of the past have developed problems, such as the emergence and potential spread of super pathogens resistant to available antibiotic arrays. One common feature of a complex system is its emergent properties—thecollectiveresultofdistinctandinteractiveproperties generated by the interaction of individual components. When parts change, the behavior of a system can sometimes be predicted—but often cannot be if the system exists on the “edge of chaos.” For example, a disconnect exists between the status of the parts (such as tumor response) and the systems behavior(suchasoverall survivalof thepatient).Furthermore, nonlinear responsesof a complexsystemcanundergosudden massive and stochastic changes in response to what may seem minor perturbations. This may occur despite the same system displaying regular and predictable behavior under other conditions. For example, patients can be harmed by an uncommonadverseeffectofacommonlyusedtreatmentwhenthesystemdisplayschaoticbehaviorundersomecircumstances.This stochastic effect is what causes surprise. Given that any medical intervention is a stress to the system and that multiple system levels can respond differently, researchers must consider the stochastic response of the entire human system to drug therapyrather thanfocusingsolelyonthetargetedorganorcell oroneparticularmolecularpathwayorspecificgene.Thesame approachisnecessaryformonitoringtheclinicalsafetyofadrug. Other challenging questions await consideration. Once an entire systemisalteredbydiseaseprogression,howshould the system be restored following replacement of a defective part? If a system is altered, should it be brought back to the previous status, or is there a new standard defining a new stable system?Thedevelopmentofmanydiseasescantakeyears,during which time the system has adapted to function in the altered environment. These changes are not restricted to a few clinicallymonitored factorsbut can involve thewhole system, which now has adapted a new homeostasis with new dynamic interactions. Restoring only a few factors without considering the entire system can often result in further stress to the system, which might trigger a decline in system chaos. For many disease conditions resulting from years of adaptation, gradual