Anopheles and Plasmodium: Immunogenomics of Vector / Pathogen Interactions
Discovering the links between the genome and the immune system is important because people with autoimmune diseases are currently treated with drugs that suppress immunity, and as a result, they are vulnerable to infection with other diseases. The group is looking at 10, samples, collected from patients in each of diseases, in the hopes of diagnosing diseases earlier, developing new and better therapy options, and identifying opportunities for new vaccines. Immunogenomics bringing together scientists at intersection of genomics, immunology Posted on September 23rd, Increased burden of de novo predicted deleterious variants in complex congenital diaphragmatic hernia.
Develop computational methods to identify and interpret genetic variations from genome sequencing data. Ongoing projects include detecting copy number variants and structural variants from exome or genome sequencing data, accurate estimation of genotype likelihood from sequencing data using deep learning, predicting genetic effect of missense or noncoding variants.
MVP: predicting pathogenicity of missense variants by deep learning. A SNP discovery method to assess variant allele probability from next generation resequencing data. Computational analysis and mathematical modeling to understand dynamics of immune cells in human. There is a strong need to recruit clinical scientists into an ecosystem to develop innovative therapies that make a genuine difference in patients. This ecosystem requires those willing to toil away at fundamental biological problems; those committed to converting biological observations into testable therapeutic hypotheses in humans; and those who develop therapies and gain approval from regulatory agencies throughout the world.
The first step is largely done in academic settings, and the other two steps largely done in the biopharmaceutical industry…although I am sure there are many who would disagree with this gross generalization!
- Immunogenomics of Disease: Accelerating to Patient Benefit.
- Immunogenomics of Disease: Accelerating to Patient Benefit!
- Geometry of Group Representations: Proceedings.
- Final Report Summary - IMMUNO (Immunogenomics: Mouse to Human Translational Research).
- The nature of mathematical modeling.
Many of you are probably fully aware of how immuno-oncology is changing cancer treatment. More recently, Genome Magazine had a feature article on the history of immunotherapy here. Cancer immunotherapy is really cool! I admit upfront that this is a self-serving blog, as it promotes a manuscript for which I was directly involved.
6th Annual Immunogenomics Conference at HudsonAlpha
But I do think it represents a very nice example of the role of human genetics for drug discovery. The concept, which I have discussed before including my last blog , is that there is a four-step process for progressing from a human genetic discovery to a new target for a drug screen.
Before I provide a summary of the study, I would like to highlight a few recent news stories that highlight that the world thinks this type of information is valuable. Oliver Sacks has terminal cancer.
- Bible and Cinema: Fifty Key Films (Routledge Key Guides).
- The Distribution of Diffracting Power in Sodium Chloride.
In his essay, Dr. So why do I blog, tweet, etc. I enjoy the public exchange of ideas because, as Dr.
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I enjoy a network of inter-related ideas for which I can create unique connections. Imagine you live in Boston or New York. It is Monday January 26, You are watching headlines of an impending blizzard, trying to figure out the truth about the weather for the next day. You find that the National Weather Service has a cool online tool — experimental probabilistic snow forecast see here. As described in Slate magazine see here , this tool predicted a 67 percent chance of at least 18 inches in New York City.
Unfortunately, most people interpreted this data that there would be 18 inches of snow, not that there could be with a certain probability 18 inches of snow. It was not until Mother Nature did her experiment that we saw the outcome: not much snow in the Big Apple, more than 2 feet of snow in Boston. The analogy with human genetics is this: it is possible to forecast the functional consequences of deleterious mutations, but it is not until the experimental snow falls — molecular or cellular experiments revealing the functional consequences of mutations — that the functional consequences are actually known.
And without knowing the functional consequences of mutations, it is difficult to determine the association of these mutations with human disease. So far, we are 2 for 2. That is, this is the second week in a row where we have reviewed the literature for interesting journal articles and written a blog on why the study is relevant for drug discovery. We received a number of interesting submissions from GpGx team members, as summarized at the end of the blog. Summary of the manuscript : While patients with congenital Factor XI deficiency have a reduced risk of venous thromboembolism VTE , it is unknown whether therapeutic modulation of Factor XI will prevent venous thromboembolism without increasing the risk of bleeding.
In this open-label, parallel-group study, patients who were undergoing elective primary unilateral total knee arthroplasty were randomly assigned to receive one of two doses of FXI-ASO mg or mg or 40 mg of enoxaparin once daily. I believe that humans represent the ideal model organism for the development of innovative therapies to improve human health. Experiments of nature e. Using my Twitter account rplenge , this blog www. Why do drugs fail whydrugsfail?
Anopheles and Plasmodium: Immunogenomics of Vector / Pathogen Interactions | IRB Barcelona
This simple question is at the center of problems facing the pharmaceutical industry. In short, drugs fail in early development because of unresolved safety signals or lack of biomarkers for target engagement, and drugs fail in late development because of lack of efficacy or excess toxicity. Without improvements in rates of success in drug development, the sustainability of the pharmaceutical industry as we know it is in trouble see here. Not surprisingly, much has been written about this topic, including analyses of development strategies Forbes blog , Drug Baron , company pipelines Nature Reviews Drug Discovery manuscript from AstraZeneca and FDA approvals here and here.
At the Spring PGRN meeting last week, there were a number of interesting talks about the need for new databases to foster genetics research. One talk was from Scott Weiss on Gene Insight see here.
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- Bless Me, Ultima (Cliffs Notes).
Here are a few general thoughts about the databases we need for genomics research. Too often, data from one interesting pharmacogenomic study e. Yes, specialized labs that generated the data can integrate the data for their own analysis. And yes, they can release individual datasets into the public for others to stitch together.