Personalized medicine : the impact on chemistry

An effective strategy for personalized medicine requires a major conceptual change in the development and application of therapeutics. In this article, we argue that further advances in this field should be made with reference to another conceptual shift, that of network pharmacology. We examine the intersection of personalized medicine and network pharmacology to identify strategies for the development of personalized therapies that are fully informed by network pharmacology concepts. This provides a framework for discussion of the impact personalized medicine will have on chemistry in terms of drug discovery, formulation and delivery, the adaptations and changes in ideology required and the contribution chemistry is already making. New ways of conceptualizing chemistry’s relationship with medicine will lead to new approaches to drug discovery and hold promise of delivering safer and more effective therapies

Factors that Lead to the Immunotherapy Gap in Multiple Sclerosis Testing

Multiple sclerosis is a disease that affects the central nervous system. Most doctors and scientists believe that it is an autoimmune disease. Simply put, the immune system attacks the nerves in a person’s body, thereby causing myelin damage, inflammation, and neurodegeneration. The plaque that then builds up on the nerves is scar tissue created when the wounds made by the immune system heal. It is this plaque that inhibits communication between the axons in the body and causes the symptoms of MS, which includes problems with movement, pain, vision problems, trouble swallowing, fatigue, and heat sensitivity (Baker et al., 2011, p. 647)

Populational adaptive evolution, chemotherapeutic resistance and multiple anti-cancer therapies

Resistance to chemotherapies, particularly to anticancer treatments, is an increasing medical concern. Among the many mechanisms at work in cancers, one of the most important is the selection of tumor cells expressing resistance genes or phenotypes. Motivated by the theory of mutation-selection in adaptive evolution, we propose a model based on a continuous variable that represents the expression level of a resistance gene (or genes, yielding a phenotype) influencing in healthy and tumor cells birth/death rates, effects of chemotherapies (both cytotoxic and cytostatic) and mutations. We extend previous work by demonstrating how qualitatively different actions of chemotherapeutic and cytostatic treatments may induce different levels of resistance. The mathematical interest of our study is in the formalism of constrained Hamilton-Jacobi equations in the framework of viscosity solutions. We derive the long-term temporal dynamics of the fittest traits in the regime of small mutations. In the context of adaptive cancer management, we also analyse whether an optimal drug level is better than the maximal tolerated dose

Natural selection and genetic variation in a promising Chagas disease drug target: Trypanosoma cruzi trans-sialidase

Rational drug design is a powerful method in which new and innovative therapeutics can be designed based on knowledge of the biological target aiming to provide more efficacious and responsible therapeutics. Understanding aspects of the targeted biological agent is important to optimize drug design and preemptively design to slow or avoid drug resistance. Chagas disease, an endemic disease for South and Central America and Mexico is caused by Trypanosoma cruzi, a protozoan parasite known to consist of six separate genetic clusters or DTUs (discrete typing units). Chagas disease therapeutics are problematic and a call for new therapeutics is widespread. Many researchers are working to use rational drug design for developing Chagas drugs and one potential target that receives a lot of attention is the T. cruzi trans-sialidase protein. Trans-sialidase is a nuclear gene that has been shown to be associated with virulence. In T. cruzi, trans-sialidase (TcTS) codes for a protein that catalyzes the transfer of sialic acid from a mammalian host coating the parasitic surface membrane to avoid immuno-detection. Variance in disease pathology depends somewhat on T. cruzi DTU, as well, there is considerable genetic variation within DTUs. However, the role of TcTS in pathology variance among and within DTU’s is not well understood despite numerous studies of TcTS. These previous studies include determining the crystalline structure of TcTS as well as the TS protein structure in other trypanosomes where the enzyme is often inactive. However, no study has examined the role of natural selection in genetic variation in TcTS. In order to understand the role of natural selection in TcTS DNA sequence and protein variation, we sequenced 540 bp of the TcTS gene from 48 insect vectors. Because all 48 sequences had multiple polymorphic bases, we examined cloned sequences from two of the insect vectors. The data are analyzed to understand the role of natural selection in shaping genetic variation in TcTS and interpreted in light of the possible role of TcTS as a drug target

Stroke genetics: prospects for personalized medicine.

Epidemiologic evidence supports a genetic predisposition to stroke. Recent advances, primarily using the genome-wide association study approach, are transforming what we know about the genetics of multifactorial stroke, and are identifying novel stroke genes. The current findings are consistent with different stroke subtypes having different genetic architecture. These discoveries may identify novel pathways involved in stroke pathogenesis, and suggest new treatment approaches. However, the already identified genetic variants explain only a small proportion of overall stroke risk, and therefore are not currently useful in predicting risk for the individual patient. Such risk prediction may become a reality as identification of a greater number of stroke risk variants that explain the majority of genetic risk proceeds, and perhaps when information on rare variants, identified by whole-genome sequencing, is also incorporated into risk algorithms. Pharmacogenomics may offer the potential for earlier implementation of 'personalized genetic' medicine. Genetic variants affecting clopidogrel and warfarin metabolism may identify non-responders and reduce side-effects, but these approaches have not yet been widely adopted in clinical practice