Introducing Patterns of Variability for Overcoming Compensatory Adaptation of the Immune System to Immunomodulatory Agents: A Novel Method for Improving Clinical Response to Anti-TNF Therapies

Abstract

Primary lack of response and secondary loss of response (LOR) are major obstacles to the use of anti–tumor necrosis factor (TNF)-based therapies in patients with rheumatoid arthritis or inflammatory bowel disease. Here, we review the mechanisms and methods for predicting LOR and the currently used methods for overcoming the ineffectiveness of anti-TNFs. The complex functions of TNF and anti-TNF antibodies, which can promote both pro- or anti-inflammatory actions, and the factors that affect the induction of immune tolerance to their effects are presented. The lack of rules and the continuous dynamics of the immune processes partly underlie the unpredictability of the response to anti-TNFs. Variability is inherent to biological systems, including immune processes, and intra/inter-patient variability has been described in the response to drugs. This variability is viewed as a compensatory adaptation mechanism of the immune system in response to drugs and may contribute to treatment LOR. Dose reductions and drug holidays have been tested in patients treated with anti-TNFs. Regular dose-based regimens may be incompatible with physiological variability, further contributing to treatment inefficacy. We present the concept of overcoming immune system adaptation to anti-TNFs by introducing patient-tailored patterns of variability to treatment regimens.

Order Through Disorder: The Characteristic Variability of Systems

“…Variability in biological systems can be viewed as a contributing modality of their function (Clarke and Crame, 2010;Farahpour et al, 2018). Randomness can be considered as a property of causal processes, contributing to complex system function (Ilan, 2019e;Kenig and Ilan, 2019;Khoury and Ilan, 2019). Random genetic drift is accepted as the random fluctuations in the numbers of gene variants in a population (Lynch et al, 2016).…”

“…The optimal state in variability may have a U shape between a chaotic pattern of variability in a steady state and full predictability in a normal biological system (Stergiou and Decker, 2011;Ilan, 2019a,b,c,e,f). Dosing of medications using regular fixed regimens may not be compatible with the physiological variability in the immune system and may further contribute to loss of response (Weiner et al, 1980;Toni and Tidor, 2013;Ilan, 2019c;Kenig and Ilan, 2019;Khoury and Ilan, 2019).…”

“…Under certain conditions, promoting or making use of variability-associated parameters, may be necessary for improving the function of processes and systems (Ilan, 2019f). It was also proposed to be use as a method for improving and/or correcting malfunction or disease states (El-Haj et al, 2019;Ilan, 2019d,f;Kenig and Ilan, 2019;Khoury and Ilan, 2019).…”

Targeting SARS-CoV-2 receptors as a means for reducing infectivity and improving antiviral and immune response: an algorithm-based method for overcoming resistance to antiviral agents

“…The unpredictability of drug effectiveness is partly associated with the dynamicity and continuously changing rules by which these systems function. Dosing regimens of drugs, which are based on regular fixed schedules, have been proposed to be incompatible with the physiological variability by which these systems operate, leading to primary or secondary loss of response [92,93].…”

“…A patient-tailored approach, which implements personalized variability patterns into treatment algorithms, has been proposed to improve the treatment sustainability. Patterns of variability can be quantified based on host and disease-related variability patterns, immune tests, genetic profiling, chronotherapy, heart rate variability, and additional parameters [92,93]. Algorithm-controlled treatment regimens are now being used in several clinical trials for overcoming drug resistance (NCT03843697; NCT03747705).…”