Proposition of a new system of medicine based on tolerance principle

Med Hypotheses. 2002 Aug;59(2):191-203. doi: 10.1016/s0306-9877(02)00248-7.

Abstract

The author proposes an explanatory model to modify Hahnemann's old tool--"similia similibus curantur"--and suggested a new experimental design to be used to detect the root cause of several chronic diseases and to treat them. All the biochemical reactions of an ideal cell are interlinked by enzymes like a network and shortfall of any one of them may create specific combination of symptoms (e.g., phenylketonuria, alkaptonuria, etc.), due to lack of one or more products that enables us to identify the responsible enzyme. Sometimes malsynthesis of an unknown enzyme(s) or receptors are responsible for a chronic disease and it becomes difficult to identify them by merely observing symptoms. Hence involvement of a normal healthy person ("prover") would be essential to detect it. If an inhibitor that comes from a drug is able to bring the same combination of symptoms in prover it may be predicted that the drug is able to bind and inhibit the responsible enzyme or its product. Minute doses of the same inhibitor(s) can cure the disease if it can act as the ligand of the same enzyme(s), by increasing the rate of transcription (by a positive feedback loop), to compensate the loss of product of the same. The ligand-inhibitor should be trapped in by an organic molecule, like ethanol by the process of potentization to increase the invasiveness of the medicine and to avoid detoxification mechanism, baffling of which increases the concentration of inhibitor inside the cell in course. The cells able to cope up with the stress by the operation of positive feedback loop or compensation cycle synthesize more enzymes and multiply rapidly, but those cells unable to tolerate such stress gradually perish. Thus Hahnemann's principle being dependent on the cause of symptoms becomes modified as "similia similibus curantur causosymptomically".

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adaptation, Physiological*
  • Models, Biological
  • Reproducibility of Results