Tag Archives: Pharmaceuticals

Drug Sponge: Absorbing up the problems

Posted on March 27, 2019 by | Leave a comment

https://www.youtube.com/watch?v=fQsYw5brVw8&t=7s

Chemotherapy is a well-known treatment for cancer, using drugs to destroy cancer cells. However, doctors administrate these anticancer drugs with caution because they are also considered poisonous. After cancer treatments, excess drugs can stay in the human body, causing damage to healthy cells, resulting in unwanted toxic side effects. What if there was something that can absorb these drugs like a portable filter?

Various chemotherapy treatments on the growth of mesenchymal stem cells (MSC). MSC is found in bone marrow cells, that contribute to regenerating bone and muscle tissues. Source

Dr. Steven Hetts from the University of California Berkeley initially thought of an idea, to introduce a  sponge-like polymer that can absorb excess chemotherapy drugs. Sponges have immensely grown in popularity in the pharmaceutical field, as the metabolites produced hold biologically active natural products. Approximately 5300 different natural products extracted from sponges have shown pharmaceutical properties, such as anticancer and antibacterial active properties.

Schematic diagram of the developed 3D printed porous absorber. Source

In early 2019, he shared this concept among researchers from other American universities, eventually publishing a paper that describes the development of a porous absorbent polymer. The researchers built the lattice structure using 3D printing that allows the blood to circulate through the bloodstream. In addition, they coated the polymer with a polystyrenesulfonate copolymer, essential for absorbing the chemotherapy drug, doxorubicin.

Doxorubicin: a chemotherapy medication used to treat cancer. Source: Wikimedia Commons

This innovative biomedical device showed great promise, as the polymer efficiently absorbed 64±6% of the drug. Even though this was tested on pigs with healthy livers, the understanding of this device allows researchers to focus on improvements. Lattice size, the type of coating, the thickness of the coating, and the number of absorbers are all possible approaches to a more effective drug sponge.

With this in mind, doctors can potentially administrate higher doses of drugs for more aggressive tumors. In addition, modifications to the drug sponge’s coating can absorb other types of powerful chemotherapy drugs. Although testings on humans are not yet approved by the FDA, the drug sponge is a huge step towards minimizing chemotherapy toxic side effects.

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Replacing rare, costly metals in electronic and pharmaceutical applications

Posted on March 1, 2019 by | 4 comments

Some metals such as nickel, aluminum and steel are ubiquitous in our daily lives, and can be found in coinage, cookware, bridges, and more. Other metals, known as “precious metals”, are rarer and more expensive—but if you’ve ever owned a smartphone or taken medication, then you’ve likely benefitted from them as well.

An average iPhone contains approximately 0.034 grams of gold and 0.34 grams of silver, as well as smaller amounts of rare Earth elements such as yttrium, terbium, and neodymium. Precious metals are also used in the large-scale syntheses of commercial drugs. A common example is palladium, which catalyzes “cross-coupling” reactions—in which two molecules are coupled together—used to prepare Losartan (to treat high blood pressure) and Diflunisal (to treat fever and pain).

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Is Machine Learning the Future of Technology Development and Chemistry Research?

Posted on March 1, 2019 by | 4 comments

The ability for scientist to develop new drugs for everything from rare diseases to headaches is often reliant on precedent and systematic investigations. These methods are often costly and time consuming. Similar problems arise in development of new materials that may enhance our energy production. Our limited ability to rationally design materials  hampers their development. This leads to reliance on our ability to recognize the trends and behavior of already existing materials. However, what if we could amplify the ability to recognize patterns beyond human limits? Machine learning answers this problem.

A graph depicting the general algorithm machine learning follows. Source: Wikimedia Commons

While machine learning is a form artificial intelligence, our jobs are safe. Machine learning is the use of statistics and the power of computers to predict results or identify trends in data. The general method relies on the input of “training” data which is analyzed using statistics. After developing a model, information may be inferred from new data the computer encounters.

-Video Source: Google Cloud Platform educational AI Adventures Series on YouTube by Yufeng Guo in 2017.

Large technology companies have recognized the advantage of integrating machine learning into technology development. Google is one example that has successfully introduced it. Gmail uses machine learning to service 1.5 billion active accounts. They claim to detect 99.9% of phishing and spam mail from entering the user’s inbox. However, machine learning is not limited to technology companies. Chemistry researchers have quickly adopted it.

Total Number of Chemistry Publications with “Machine Learning” in Title

Starting in 1969, the first chemistry journal article with “machine learning” in the title was published. By combining machine learning with a common technique called mass spectrometry, Peter Jurs at the University of Washington was able to determine chemical composition of “unknown” chemicals using the input of 348 unique patterns as “training” data.

More recently there has been an almost exponential increase in the number of chemistry publications applying machine learning. In the last two years approximately 6 times as many publications were made than in the past 48 years. Tommi Jaakkola, a Professor of Electrical Engineering and Computer Science at MIT said at a consortium about implementing machine learning in the pharmaceutical industry: “by marrying chemical insights with modern machine learning concepts and methods, we are opening new avenues for designing, understanding, optimizing, and synthesizing drugs.” The materials science community has also seen integration with the development of novel long chained molecules called polymers for photovoltaics by scientist at Osaka University. Shinji Nagasawa, the lead author explained the importance: “there’s no easy way to design polymers with improved properties. Traditional chemical knowledge isn’t enough. Instead, we used artificial intelligence to guide the design process.”

Solar cell efficiency over years showing a substantial increase. Source: Wikimedia Commons

While machine learning is not the solution to all chemical problems or spam mail, it is being widely accepted by the scientific community and technology industry for good reasons. Even with limitations, it’s effectiveness across a wide array of industry and research emphasizes the role it may play in the future of research and development.

—Jonah

References

  1. Graph-powerd Machine Learning at Google. Google AI Blog. https://ai.googleblog.com/2016/10/graph-powered-machine-learning-at-google.html (Accessed Feb 28, 2019).
  2. Jurs, P.C.; Kowalski, B.R.; Isenhour, T.L. Computerized Learning Machines Applied to Chemical Problems: Molecular Formula Determination From Low Resolution Mass Spectrometry. Chem. 1967, 41, 21-27.
  3. Machine Learning, Materials Science and the New Imperial MOOC. Imperial College London. https://www.imperial.ac.uk/news/187054/machine-learning-materials-science-imperial-mooc/ (Accessed Feb 28, 2019).
  4. UBC Summons. University of British Columbia.

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