I'm posting here the Introduction. The full book is available on Amazon at $64.00 and perhaps represents the best Christmas gift ever and a must for your library (if you are my mother). Otherwise, if you are just curious to see how evolution tools (i.e., taxonomy) can be oddly applied to drug classification, have a try.
In spite of the progress of modern biological research, the wealth of novel findings on human physio-pathology and the adoption of ‘omic tools’, the number of novel drugs is not increasing. On the contrary, the attrition rate in drug discovery is constantly rising. The cause of this is object of a major debate; certainly a current major limitation in drug discovery and development is the assessment of drug efficacy.
A drug therapy is efficacious when it evokes the desired biological effect. Biological effects could be physiological phenomena (i.e., muscular contraction) or molecular events (i.e., increased expression of a target gene) and usually this effect responds to drug treatment in a dose-dependent manner. Today, because of our better understanding of the complexity of the cellular biology, the assessment of efficacy in ‘molecular terms’ (useful for drug development purposes) becomes of difficult application. Most of the drugs act by binding to a cellular receptor: upon binding, drugs ‘activate’ the receptor, initiating the signaling cascade responsible for the biological effect; we know that a single drug can induce different signaling cascades, and this ability may change significantly with respect to a spatial constraint, the tissue where the drug is acting, and to a temporal constraint, the timeline over drug administration. In short, a candidate drug designed to stimulate a particular biological process, could, as expected, behave as agonist in the first week of therapy and suddenly turns to an antagonist profile (with comprehensible deleterious side effects). Likely, such a candidate drug would be discarded in the drug development pipeline: in fact, it is common for unforeseen toxic profiles to be discovered late in the pipeline, already at the level of clinical studies in humans. This is unwanted: a failure of a clinical trial is a great loss for a pharmaceutical company and, ultimately, a missed opportunity for the whole healthcare sector. A comprehensive knowledge of drug actions in space and time is pivotal for the assessment of drug efficacy; unfortunately, this is accomplished only during clinical studies.
This book discusses a concept......a concept developed during my PhD training, which is the possibility to introduce new dimensions (space and time) in pre-clinical studies by monitoring drug action on living ‘luciferase reporter-mice’. These animals start glowing when and where a drug is acting. During my formation with Adriana Maggi and Paolo Ciana, we started to develop the technology to follow drug activity in different anatomical areas several times in a day, for long period of times (months) without actually killing any animal. This new knowledge would improve drug design by disclosing potential side-effects before getting into clinical research, with clear social, ethical and economical benefits.
As working model, we choose a class of drug named SERMs. Selective Estrogen Receptor Modulators (SERMs) were conceived for post-menopausal hormonal replacement therapy to avoid estrogen unwanted effects. As their name says, SERMs activity on the cognate receptor (the Estrogen Receptor, ER) is ‘selective’ – this means that a SERM that blocks estrogen’s action in breast cells may activate estrogen’s action in other cells, such as bone. To date however, none of the SERMs developed appears to be provided of the ideal balance of ER agonist and antagonist activity. Because SERMs do not fall into distinct categories of agonists and antagonists, they represent a great proof of concept to further elaborate on the assessment of drug efficacy on space and time. Furthermore, menopause is one of those permanent conditions in which a drug is supposed to be administered chronically: the time dimension can not be further neglected.
TABLE OF CONTENTS
- Classification of drug efficacy needs a revision
- Pluri-dimensions in Estrogen biology
- Hormonal Replacement Therapy: state of the art
- Do we have appropriate tools to design new HRTs?
- Better biomarkers of ER activity?
- Advantages of reporter mice in drug discovery and development
- Design criteria for better reporter mice
- The ERE-luc reporter mouse
PRACTICAL EXAMPLE #1 – VALIDATION OF A DRUG REPORTER MOUSE
- Protocols for bioluminescence imaging (BLI)
- Automated mouse segmentation
- Response to E2 (time-response)
- Response to E2 (dose-response)
- Response to Ovarectomy
- Response to ERα and ERβ agonists
- Response to SERMs
- Systematic management of BLI datasets
PRACTICAL EXAMPLE #2 – PROFILING OF SERMS FOR HORMONE REPLACEMENT THERAPY
- Dynamics of ER activity upon HRT
- Continous exposure, discontinous activity
- The dynamics of ER activity
- Taxonomy of SERM activity
- Reverse medicinal chemistry?
Appendix 1 – Materials and Methods
Appendix 2 – References
Taxonomy of Drug Activity in Vivo
Paperback, 80 Pages