Gestational Diabetes Increases Heart Disease Risk in Babies

CAITLIN WILLIAMS | July 22, 2018

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Gestational diabetes occurs in pregnant women who have high blood glucose (sugar) levels and have not previously had diabetes, usually around the 24th week. A 2014 study from the Center for Disease Control stated that gestational diabetes prevalence is as high as 9.2%. Gestational diabetes can affect both mothers and unborn children, a recent study has shown that gestational diabetes may increase the risk of heart disease in offspring.

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OTHER ARTICLES

Roche Prepares to Launch COVID-19 Antibody Test System

Article | April 17, 2020

Swiss pharma giant Roche is joining the race to develop a test for COVID-19 antibodies in people who have been exposed to the disease. This morning, Roche announced the development and upcoming launch of its Elecsys Anti-SARS-CoV-2 serology test to detect antibodies in people who have been exposed to the SARS-CoV-2, the virus that causes COVID-19. Roche is eying May for the launch of the test in Europe and is in talks with the U.S Food and Drug Administration for emergency approval of the system. Antibody testing is central to help identify people who have been infected by the virus, especially those who may have been infected but did not display symptoms, the company said. Roche noted that as more information becomes available about immunity levels to COVID-19, society can return to a sense of normal much more quickly. Roche’s test will join a number of other antibody tests that have recently come on the market. Earlier this month the U.S. Food and Drug Administration approved the first blood test for COVID-19 antibodies.

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Enabling Active Pharma Ingredients for Batch Balancing and Integration to SAP EWM

Article | April 6, 2020

Batch and its Classification system are two most potent weapons used in Chemical, Pharma or Medical life science industry to record the potency of a batch or technically called as Active Pharma Ingredients(API). These material consist of one or more active ingredients, concentrates, carrier materials, or impurities, and so on. The potency of the active ingredients varies from batch to batch. The active ingredient is the substance of greatest interest in the bill of materials, the proportion of which may vary from batch to batch. Therefore, during creation of a process order, the system must be able to select and adjust the batches needed to obtain the required amount of active ingredient. Take an example of a drug hydroxychloroquine which is used as potent weapon to fight COVID-19. This drug is manufactured by using API, however, the Potency of this API material vary from batch to batch. To map this kind of requirement in SAP ERP, SAP calls it as Material Quantity Calculation.

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New Dimensions of Clinical Trial Optimization

Article | April 20, 2021

For much of the past three decades, even as methodologies for clinical trial design have advanced and refined, the idea of the optimized clinical trial has centered on optimal patient samples, target enrollment rates, and generally the most efficient uses of scarce resources in the form of patients. Yet anyone who has had to design and optimize a clinical trial, knows that trial optimization occurs within an ecosystem of choices; a series of choices that stretch from the time it takes to implement a clinical trial and submit clinical data for analysis, to general concerns about the cost and power of a clinical trial. A true clinical trial optimization process would try to unify a number of these choices into a single framework for trial optimization. The complexity of clinical trial optimization comes from the need to align priorities on the one hand, and to understand opportunities on the other. We know that at a very general level, clinical operations specialists benefit from simplicity in clinical trial design, and that commercial teams prefer shorter clinical trials to longer ones. We also know that the statistical design of a clinical trial can influence both simplicity and duration. Yet how many sponsors have their clinical operations and commercial teams, sit with their R&D teams to review various statistically nuanced design options? For many sponsors, the reason this process does not occur as often as it should, is because the nuanced statistical parameters of a clinical trial design are very difficult to communicate to non-statisticians. Yet a trial optimization tool like Solara, equipped with data visualizations and the ability to see tradeoffs intuitively, can overcome this challenge. The real challenge is often convincing the non-statistician that they have a stake in clinical trial design. Cytel recently had a client that thought it needed a sample size re-estimation design, because it had a very strict limit on the number of patients it could enroll. After a few hours of working with Solara, though, a statistician discovered that a much simpler Group Sequential Design would deliver comparable power using about the same number of patients. The gains from the more complex design were minimal from the optimization perspective, when understood as the eco-system of choices. Similarly, most commercial teams pressure their clinical trial designers to have the most accelerated clinical trial imaginable, but as we all know, the longer the clinical trial the more likely there will be a higher number of events that demonstrate the effectiveness of a new medicine. So commercialization teams have a stake in longer clinical trials, even when their rule of thumb is to shorten them. Therefore, it is absolutely essential to communicate the benefits of various statistical designs to multiple stakeholders in a way that makes tradeoffs clear. Aligning on priorities early during the clinical trial design process is essential to selecting the optimal clinical trial. Yet for this statisticians need to be equipped for both a strategic and communicative role in the R&D process.

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Clinical Development Risks and Issues in a COVID-19 World

Article | March 20, 2020

Global clinical guidelines have shifted the industry toward risk-based approaches for the planning and execution of clinical trials. The ICH’s guidelines for Good Clinical Practice state that sponsors should evaluate identified risks against existing risk controls by considering “the likelihood of errors occurring, the extent to which such errors would be detectable, and the impact of such errors on human subject protection and reliability of trial results” (ICH E6 R2).

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