improvement
-
Scientists re-writes FDA-recommended equation to improve estimation of drug-drug interaction
Drugs absorbed into the body are metabolized and thus removed by enzymes from several organs like the liver. How fast a drug is cleared out of the system can be affected by other drugs that are taken together because added substance can increase the amount of enzyme secretion in the body. This dramatically decreases the concentration of a drug, reducing its efficacy, often leading to the failure of having any effect at all. Therefore, accurately predicting the clearance rate in the presence of drug-drug interaction* is critical in the process of drug prescription and development of a new drug in order to ensure its efficacy and/or to avoid unwanted side-effects.
*Drug-drug interaction: In terms of metabolism, drug-drug interaction is a phenomenon in which one drug changes the metabolism of another drug to promote or inhibit its excretion from the body when two or more drugs are taken together. As a result, it increases the toxicity of medicines or causes loss of efficacy.
Since it is practically impossible to evaluate all interactions between new drug candidates and all marketed drugs during the development process, the FDA recommends indirect evaluation of drug interactions using a formula suggested in their guidance, first published in 1997, revised in January of 2020, in order to evaluate drug interactions and minimize side effects of having to use more than one type of drugs at once.
The formula relies on the 110-year-old Michaelis-Menten (MM) model, which has a fundamental limit of making a very broad and groundless assumption on the part of the presence of the enzymes that metabolizes the drug. While MM equation has been one of the most widely known equations in biochemistry used in more than 220,000 published papers, the MM equation is accurate only when the concentration of the enzyme that metabolizes the drug is almost non-existent, causing the accuracy of the equation highly unsatisfactory – only 38 percent of the predictions had less than two-fold errors.
“To make up for the gap, researcher resorted to plugging in scientifically unjustified constants into the equation,” Professor Jung-woo Chae of Chungnam National University College of Pharmacy said. “This is comparable to having to have the epicyclic orbits introduced to explain the motion of the planets back in the days in order to explain the now-defunct Ptolemaic theory, because it was 'THE' theory back then.”
< (From left) Ph.D. student Yun Min Song (KAIST, co-first authors), Professor Sang Kyum Kim (Chungnam National University, co-corresponding author), Jae Kyoung Kim, CI (KAIST, co-corresponding author), Professor Jung-woo Chae (Chungnam National University, co-corresponding author), Ph.D. students Quyen Thi Tran and Ngoc-Anh Thi Vu (Chungnam National University, co-first authors) >
A joint research team composed of mathematicians from the Biomedical Mathematics Group within the Institute for Basic Science (IBS) and the Korea Advanced Institute of Science and Technology (KAIST) and pharmacological scientists from the Chungnam National University reported that they identified the major causes of the FDA-recommended equation’s inaccuracies and presented a solution.
When estimating the gut bioavailability (Fg), which is the key parameter of the equation, the fraction absorbed from the gut lumen (Fa) is usually assumed to be 1. However, many experiments have shown that Fa is less than 1, obviously since it can’t be expected that all of the orally taken drugs to be completely absorbed by the intestines. To solve this problem, the research team used an “estimated Fa” value based on factors such as the drug’s transit time, intestine radius, and permeability values and used it to re-calculate Fg.
Also, taking a different approach from the MM equation, the team used an alternative model they derived in a previous study back in 2020, which can more accurately predict the drug metabolism rate regardless of the enzyme concentration. Combining these changes, the modified equation with re-calculated Fg had a dramatically increased accuracy of the resulting estimate. The existing FDA formula predicted drug interactions within a 2-fold margin of error at the rate of 38%, whereas the accuracy rate of the revised formula reached 80%.
“Such drastic improvement in drug-drug interaction prediction accuracy is expected to make great contribution to increasing the success rate of new drug development and drug efficacy in clinical trials. As the results of this study were published in one of the top clinical pharmacology journal, it is expected that the FDA guidance will be revised according to the results of this study.” said Professor Sang Kyum Kim from Chungnam National University College of Pharmacy.
Furthermore, this study highlights the importance of collaborative research between research groups in vastly different disciplines, in a field that is as dynamic as drug interactions.
“Thanks to the collaborative research between mathematics and pharmacy, we were able to recify the formula that we have accepted to be the right answer for so long to finally grasp on the leads toward healthier life for mankind.,” said Professor Jae Kyung Kim. He continued, “I hope seeing a ‘K-formula’ entered into the US FDA guidance one day.”
The results of this study were published in the online edition of Clinical Pharmacology and Therapeutics (IF 7.051), an authoritative journal in the field of clinical pharmacology, on December 15, 2022 (Korean time).
Thesis Title: Beyond the Michaelis-Menten: Accurate Prediction of Drug Interactions through Cytochrome P450 3A4 Induction (doi: 10.1002/cpt.2824)
< Figure 1. The formula proposed by the FDA guidance for predicting drug-drug interactions (top) and the formula newly derived by the researchers (bottom). AUCR (the ratio of substrate area under the plasma concentration-time curve) represents the rate of change in drug concentration due to drug interactions. The research team more than doubled the accuracy of drug interaction prediction compared to the existing formula. >
< Figure 2. Existing FDA formulas tend to underestimate the extent of drug-drug interactions (gray dots) than the actual measured values. On the other hand, the newly derived equation (red dot) has a prediction rate that is within the error range of 2 times (0.5 to 2 times) of the measured value, and is more than twice as high as the existing equation. The solid line in the figure represents the predicted value that matches the measured value. The dotted line represents the predicted value with an error of 0.5 to 2 times. >
For further information or to request media assistance, please contact Jae Kyoung Kim at Biomedical Mathematics Group, Institute for Basic Science (IBS) (jaekkim@ibs.re.kr) or William I. Suh at the IBS Communications Team (willisuh@ibs.re.kr).
- About the Institute for Basic Science (IBS)
IBS was founded in 2011 by the government of the Republic of Korea with the sole purpose of driving forward the development of basic science in South Korea. IBS has 4 research institutes and 33 research centers as of January 2023. There are eleven physics, three mathematics, five chemistry, nine life science, two earth science, and three interdisciplinary research centers.
2023.01.18 View 9716 -
KAIST Earns AACSB Business School Accreditation
The KAIST College of Business re-earned business school accreditation from the Association to Advance Collegiate Schools of Business (AACSB) International. The school first earned the accreditation in 2003, and has continued to receive the accreditation four consecutive times. Currently only 5% of the 16,000 business schools around the world have earned AACSB accreditation. KAIST received a good evaluation for the competitive research of its faculty, its executive education programs based on strong industry-academia ties, and specialized MBA and master’s program, which includes programs such as social entrepreneurship and green business and policy.Alexander Triantis, dean of the Robert H. Smith School of Business at the University of Maryland and a judge for AACSB Accreditation said, “I was impressed to see students from KAIST have a high standard of knowledge. A number of its graduates continue to be appointed as professors of top universities abroad, which shows its strong global competence”. AACSB was founded in 1916 by deans of business colleges from prestigious universities such as Harvard University, Stanford University and Columbia University, to provide business and accounting accreditation to universities. Evaluation for AACSB accreditation takes place every five years. Schools are evaluated based on fifteen standards, including student admission and graduation requirements, student-faculty ratios, faculty’s intellectual contributions, research infrastructure, global cooperation, and industry-academia programs. They can be eligible for re-accreditation if they satisfy the conditions offered by AACSB International and are committed to continuous improvement every five years. KAIST also earned the accreditation from the European Foundation for Management Development Quality Improvement System (EQUIS) three consecutive times since 2010. In 2013, it earned membership into the Partnership in International Management (PIM). Membership is only possible for those who have AACSB and EQUIS accreditation and they can be listed as a candidate school through voting. The candidate schools can finally earn membership after one year of strict screening. As of January 2019, there are 65 prestigious graduate schools of business, including KAIST, listed as PIM members.
2019.02.01 View 4897 -
Professor Poong Hyun Seong Selected as Fellow of the ANS
Professor Poong Hyun Seong of the Department of Nuclear and Quantum Engineering was selected as a fellow of the American Nuclear Society.
The selection was announced at their annual meeting held in San Francisco on June 12, in recognition of Professor Seong's contributions to the field of nuclear instrumentation, control andhuman factors engineering.
Founded in 1954, the American Nuclear Society selects scholars who have made outstanding achievements and contributions to the development of the nuclear engineering field each year.
Professor Seong's researches in the field of nuclear instrumentation, control and human factors engineering have contributed to the safe operation of nuclear power plants, to the development of systems to maintain nuclear power plants safely in the event of emergency and to the enhancement of effective response capabilities of nuclear power plant operators. His researches significantly contributed to the safety improvement of nuclear power plants and have been recognized worldwide.
Professor Seong said, "Korea has emerged as a nuclear powerhouse. I think not only my academic career but our national reputation in the field of nuclear research has been well recognized by our global peers.” Professor Seong has served as president of the Korean Nuclear Society, editor in chief of Nuclear Engineering and Technology, and as a commissioner of the Korean Nuclear Safety Commission. He is currently working as a commissioner of the Korean Atomic Energy Commission.
2017.06.29 View 6453 -
Jang Young Shin Chairwoman of AeKyung Group donates 3billion Won to KAIST
AeKyung Group donated 3 billion Won for the development of KAIST and the betterment of Korea’s Science. The ceremony was held on the 2nd of May with President Seo Nam Pyo of KAIST and Jang Young Shin Chairwoman of AeKyung Group in attendance.
Chairwoman Jang insisted that the donation be used for the establishment of a stable study environment at KAIST and the improvement of student welfare.
Chairwoman Jang is a CEO with an engineering background. She majored in Chemistry in Chestnut Hill College with National Scholarship in 1950 and established the AeKyung Group’s many subsidiaries that deal with Chemicals.
2011.05.11 View 9475 -
KAIST Professors Article Featured as Cover Thesis of Biotechnology Journal
An article authored by a research team of Prof. Sang-yup Lee at the Department of Chemical and Biomolecular Engineering and Dr. Jin-Hwan Park at the KAIST Institute for the BioCentury has been featured as the cover thesis of the August 2008 issue of Trends in Biotechnology.
The paper, titled "General strategy for strain improvement by means of systems metabolic engineering," focuses on the application of systems biology for the development of strains and illustrates future prospects. Trends in Biotechnology, published by Cell Press, is one of the most prestigious review journals in the field.
Jin-Hwan Park, the primary author of the research thesis, said that the KAIST team"s research work was expected to provide substantial help to researchers involved in biotechnology industry.
The strategy has been established on the basis of the experiences gained in the actual microbial production process using the systems biology methods which his research team has recently worked on, Prof. Park said.
2008.07.24 View 13815
-
Youngseok Son and Yongjoon Chun won a prize of Commerce, Industry and Energy Minister
Youngseok Son and Yongjoon Chun won a prize of Commerce, Industry and Energy Minister
Youngseok Son and Yongjoon Chun, doctorate students at circuit design and system application lab of Electrical Engineering Division, won a prize of Commerce, Industry and Energy Minister (Silver prize) at the 7th Semiconductor Design Contest hosted by the Korean Intellectual Property Office.
Their work exhibited at the contest is ‘a driving circuit for the improvement of image quality of AMOLED display’.
AMOLED display is gaining attention as a next-generation display for its numberless advantages compared to AMLCD and PDP, however, problems over the image quality and lifespan of the display have disturbed the substantial development. Their work verified its electrical features by proposing and designing the driving method and circuit for the improvement of the image quality and lifespan of AMOLED display. The announced driving method was named ‘Transient Cancellation Feedback (FCF)’ and its concept was published in SID 2006. Their work was evaluated to overcome the limitation of the existing driving methods by providing an intrinsic Active Matrix structure, different from the existing driving methods.
It is also evaluated to strikingly enhance the speed and accuracy of data current driving through TCF driving. It is expected to significantly enhance the image quality and lifespan of AMOLED displays by applying TCF driving.
2006.11.27 View 14985