Tag: computer modelling

Categories : GastrointestinalTags :

Body Posture, Stomach Motility Affect Oral Pill Bioavailability

On By ModernMedia
Photo by danilo.alvesd on Unsplash

While oral administration of a pill or capsule is a simple and cheap route, it is also the most complex way for the human body to absorb an active pharmaceutical ingredient, due to the stomach environment’s influence on bioavailability. Using highly detailed computer simulations, researchers have now found that stomach motility and posture (leaning right, left or backwards) significantly affect bioavailability.

The rate of dissolution and gastric emptying of the dissolved active pharmaceutical ingredient (API) into the duodenum is modulated by gastric motility, physical properties of the pill, and the contents of the stomach. This results in varying rates of pill dissolution and nonuniform emptying of the drug into the duodenum and, occasionally, gastric dumping in the case of modified-release dosage. Current in vitro procedures for assessing dissolution of oral drugs do not simulate this process well.

In Physics of Fluids, researchers used a biomimetic computer simulation based on the realistic anatomy and morphology of the stomach (a ‘StomachSim’) to investigate and quantify the effect of body posture and stomach motility on drug bioavailability over the first few minutes of absoprtion.

 The simulations show that changes in posture can potentially have a significant (up to 83%) effect on the emptying rate of the API into the duodenum. A 45 degree lean to the left greatly reduced the amount of active ingredient per cycle released into the duodenum, while a lean to the right dramatically increased it over the upright case.

Similarly, the researchers found that a reduction in antral contractility associated with gastroparesis significantly reduced the dissolution of the pill as well as emptying of the API into the duodenum. The simulations show that for an equivalent motility index, the reduction in gastric emptying due to neuropathic gastroparesis is larger by a factor of about five compared to myopathic gastroparesis.

“Oral administration is surprisingly complex despite being the most common choice for drug administration,” said co-author Rajat Mittal. “When the pill reaches the stomach, the motion of the stomach walls and the flow of contents inside determine the rate at which it dissolves. The properties of the pill and the stomach contents also play a major role.

“However, current experimental or clinical procedures for assessing the dissolution of oral drugs are limited in their ability to study this, which makes it a challenge to understand how the dissolution is affected in different stomach disorders, such as gastroparesis, which slows down the emptying of the stomach.”

Together, these issues pose several challenges for the design of drug delivery.

“In this work, we demonstrate a novel computer simulation platform that offers the potential for overcoming these limitations,” said Mittal. “Our models can generate biorelevant data on drug dissolution that can provide useful and unique insights into the complex physiological processes behind the oral administration of pills.”

The researchers note that the simulation required a lot of computational time, only capturing the first few minutes of the process, and are working on faster methods to capture differences over the period of an hour.

Source: American Institute of Physics

Categories : Diseases, Syndromes and ConditionsTags :

Oil Exploration Software Reveals why Cystic Fibrosis Drugs Fail

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Photo by WORKSITE Ltd. on Unsplash

Scientists have harnessed a computational approach usually used in oil exploration to search for cures for rare genetic diseases such cystic fibrosis. By using the method to analyse the spatial relationships between different variants of a protein, instead of the relationships between test wells across an oil field, the researchers can obtain valuable information on how disease affects a protein’s underlying shape and how drugs can restore that shape to normal.

The new method, detailed in the journal Structure, runs with just a few gene sequences collected from people with disease. Then, it determines how the structure of each corresponding variant protein is associated with its function, and how this functional structure can affect pathology and be repaired by therapeutics. To test the techniques, the researchers showed why existing drugs for cystic fibrosis fall short of curing the disease.

“This is an important step forward for treating rare diseases,” said senior author William Balch, PhD, professor of Molecular Medicine at Scripps Research. “The fact that we can get so much information from a few gene sequences is really unprecedented.”

Studies on inherited diseases often rely on the precise three-dimensional shape of a protein affected by disease. But genetic diseases can be caused by thousands of gene variants, some of which destabilise or change the protein shape in ways that make isolating the protein for further investigation much more difficult than usual.

Prof Balch, with Scripps Research senior staff scientist Chao Wang and staff scientist Frédéric Anglés, instead wanted to use natural variation to their advantage. So the group developed a method called variation-capture (VarC) mapping to analyse the natural array of gene sequences which exist in the human population and determine the mechanism by which they each changed a protein’s structure to cause disease.

Among other statistical tools, Prof Balch’s group integrated the methods that oil companies use to draw inferences about the location of an oil reservoir using only a small number of test wells. With only a few gene sequences, this let the researchers determine the most likely structural mechanisms driving function for each variant leading to disease, as well as model how drugs impacted those structural functions.

In the case of cystic fibrosis, disease is caused by genetic variants in the cystic fibrosis transmembrane conductance regulator (CFTR), leading to a buildup of mucus in the lungs. More than 2000 variants of the CFTR gene have been identified, and many of these variants were known to have very different effects on the CFTR protein, but it has been difficult to compare and contrast these variants to guide how patients with different variants should be treated differently in the clinic.

“When you want to treat patients, you really have to appreciate that different therapeutics might target different variants in completely different ways, and that’s why our approach that looks at many different variants all at once is so powerful,” explained Wang. “Our approach not only reveals how these variants contribute to each patient’s biology, but also connects them in a way that each variant can inform how to manage the others.”

The researchers input about 60 genetic variants found in the cystic fibrosis population into their VarC program. The analysis captured how each amino acid residue talks to every other residue to generate function, and revealed that most of the cystic fibrosis patients had the same net effect on the protein: an unstable inner core.

When the program modelled how existing cystic fibrosis drugs impacted the structures, the researchers discovered that, despite the drugs’ effect on CFTR structure, none of them effectively stabilised the protein’s hidden inner core. This was like how the location of an oil reservoir in a complex landscape can be revealed by test wells.

Now that the researchers better understand the structural deficiencies in CFTR in cystic fibrosis patients, they say that the job of developing an effective drug to fix it is much easier. Potential compounds can be modelled in advance of lab experiments for their effect on the inner core of the CFTR protein.

“In most drug discovery, you throw thousands of compounds at a protein and see which ones change it, often without fully understanding the mechanism,” said Prof Balch. “To fix a thing, you must first understand the problem.”

Already, his team is applying the method to other rare genetic diseases, as well as pursuing new drugs to treat cystic fibrosis.

Source: Scripps Research Institute