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Capillary Forces at Work for Lithium-Sulfur Batteries
Professor Do Kyung Kim from the KAIST Department of Materials Science and Engineering and his team succeeded in developing high-areal-capacity lithium sulfur batteries (Li-S batteries) by capturing polysulfide with carbon nanofibers. This research will provide new batteries to replace existing lithium rechargeable batteries, shifting the commercialization of related technologies ahead.
Electrical vehicles and large-scale energy storage systems necessitate the development of batteries with high energy density and cost effectiveness, and Li-S batteries are known to be one of the promising alternatives to the predominant lithium ion batteries.
With six times as much energy density, Li-S batteries theoretically thrust electric vehicle to twice the distance of lithium ion batteries. Therefore, they have been spotlighted as next-generation lithium rechargeable batteries because they can go up to 400km once charged.
However, several issues make it challenging to readily commercialize Li-S batteries. The low electrical conductivity of sulfur, volumetric expansion and contraction of the battery during charge and discharge, and permanent damage of the electrode caused by the dissolution of the lithium polysulfide into the electrolyte – known as the “shuttle effect” – are three of the biggest obstacles to commercial-grade Li-S batteries.
While there have been numerous attempts to curb, avoid, or alleviate these issues — such as the physical encapsulation of sulfur using various metal oxides or carbonaceous matrices — most of them entail utilizing zero-dimensional (0D) carbon materials. This encapsulation method has been somewhat effective in enhancing the electrical conductivity of sulfur while simultaneously tolerating some volumetric alterations and suppressing the shuttle effect. The downside of 0D carbon material-based encapsulation methods is their complicated synthetic processing and the limited mass loading of sulfur.
With this in mind, the team set out to employ one-dimensional (1D) carbon materials instead. Unlike the 0D case, 1D carbon materials render a large surface area and a long-range conduction path for electrons and lithium ions. Being 1D also solves the undesirable high-contact resistance problem frequently encountered by 0D carbon material-based encapsulation.
The key to developing the proposed material was to exploit the capillary force to decrease the energy associated with the dissolution of polysulfides. As such, carbon nanofibers (CNFs) were found to be suitable for high-areal-capacity lithium-sulfur batteries since capillary force acting between CNFs can take advantage of the high electrical conductivity with the suppressed dissolution of sulfides.
The research findings show that sulfur was successfully contained in between the CNFs by wetting due to the capillary force without the need for complicated synthetic processing, as in the 0D case. The research results indicate that the sulfur contained per unit area (mg/cm2) is five times greater for the newly implemented method, which then enabled the lithium-sulfur battery to achieve an areal capacity of 7 mAh/cm2, which amounts to as much as at most seven times that of conventional lithium ion batteries.
First author Jong Hyuk Yun stated that the unprecedented methods utilized in this study will help further and widen the progress of lithium batteries in general. Meanwhile, Professor Kim said, “This study brought us closer to commercial-grade high-capacity Li-S batteries, which are applicable for a wide variety of products, including electric vehicles, unmanned aerial vehicles (UAVs), and drones.”
This research, led by PhD candidate Yun, was published in the 18th issue of this year’s Nano Letters.
Figure 1. Electrochemical reaction leading to the containment of the sulfur within the carbon nanofiber and the corresponding specific capacity of the battery over a number of charge-discharge cycles
Figure 2. SEM images of the first discharged electrode containing lithium sulfide at the junction between the nanofibers, and the first charged electrode
Figure 3. carbon nanofiber effectively absorbing liquid based lithium polysulfide
2018.05.14 View 7247 -
New Material for Generating Energy-Efficient Spin Currents
(Professor Byong-Guk Park (left) and Professor Kab-Jin Kim)
Magnetic random access memory (MRAM) is emerging as next-generation memory. It allows information to be kept even without an external power supply and its unique blend of high density and high speed operation is driving global semiconductor manufacturers to develop new versions continuously.
A KAIST team, led by Professor Byong-Guk Park in the Department of Materials Science and Engineering and Professor Kab-Jin Kim in the Department of Physics, recently has developed a new material which enables the efficient generation of a spin current, the core part of operating MRAM. This new material consisting of ferromagnet-transition metal bilayers can randomly control the direction of the generated spin current unlike the existing ones.
They also described a mechanism for spin-current generation at the interface between the bottom ferromagnetic layer and the non-magnetic spacer layer, which gives torques on the top magnetic layer that are consistent with the measured magnetization dependence.
When applying this to spin-orbit torque magnetic memory, it shows the increased efficiency of spin torque and generation of the spin current without an external magnetic field. High-speed operation, the distinct feature of spin-orbit torque-based MRAM that carries its non-volatility, can significantly reduce the standby power better than SRAM.
This new material will expect to speed up the commercialization of MRAM. The research team said that this magnetic memory will further be applied to mobile, wearable, and IoT devices.
This study, conducted in collaboration with Professor Kyung-Jin Lee from Korea University and Dr. Mark Stiles from the National Institute of Standards and Technology in the US, was featured in Nature Materials in March. The research was funded by the Creative Materials Discovery Program of the Ministry of Science and ICT.
(Figure: Ferromagnet-transition metal bilayers which can randomly control the direction of the generated spin current)
2018.05.11 View 8814 -
Yoon Ki Hong Named 2018 Jeong Hun Cho Awardee
(From left: PhD candidate Seungkwan Baek from the Department of Aerospace Engineering, Dr. Yoon Ki Hong from ADD, PhD candidate Wonhee Choi from the School of Mechanical Engineering at Korea University, and Jaehun Lee from Kongju National University High School)
Dr. Yoon Ki Hong from the Agency of Defense Development (ADD) was named the 2018 recipient of the Jong-Hoon Cho Award. The award recognizes outstanding young scientists in the field of aerospace engineering annually. The recipient of this award receives a 25 million KRW prize.
The Award Committee said that Dr. Hong has achieved outstanding work in the field of aerospace engineering. In particular, he conducted research on designing an air heating device which is the crucial component for ground experimental equipment. It is required for testing and evaluating supersonic vehicles’ structural strength tests using technology cannot be imported. In cooperation with his colleagues, he succeeded in developing an air heating device, a feat that has only been accomplished by developed countries. He also verified its operational performance.
Moreover, he received the best paper award from Korean Federation of Science and Minister of Defense Acquisition Program Administration’s Prize.
The award was endowed by the family of the late PhD candidate Jeong Hun Cho, who died in a rocket lab accident in the Department of Aerospace Engineering in 2003. Cho was posthumously conferred an honorary doctorate degree.
In Cho’s memory, his father established the ‘Jeong Hun Cho Award and Scholarship’. Since 2005, the scholarship annually selects three young scholars specializing in aerospace engineering from Cho’s alma maters of KAIST, Korea University, and Kongju National University High School.
In addition to Dr. Hong, the Award Committee chose three students for scholarships: PhD candidate Seungkwan Baek from the Department of Aerospace Engineering, PhD candidate Wonhee Choi from the School of Mechanical Engineering at Korea University, and Jaehun Lee from Kongju National University High School.
2018.05.11 View 8121 -
The First Recipient of the KPS Award in Plasma Physics
( Research Professor Sanghoo Park)
Research Professor Sanghoo Park received the Young Researcher Award in Plasma Physics during the Korean Physical Society (KPS)’s Spring Meeting from April 25 to 27.
He is a KAIST graduate with a PhD in Physics and currently holds the position of research professor in the Department of Nuclear and Quantum Engineering.
The Young Researcher Award in Plasma Physics is given to a specialist in plasma who has the potential to make a contribution to plasma and accelerator physics in Korea.
Professor Park has gained recognition for his work, including awards, publications in 24 journals, and 12 technical patent registrations of plasma, which led to his selection as the recipient of this award.
He is now conducting a leading role in this field nationally and internationally by delving into the study of partially-ionized plasma.
Professor Park said, “It is my great honor to become the first recipient of the Young Researcher Award in Plasma Physics. I will continue to engage in research to develop the field of plasma in Korea.”
2018.05.08 View 5465 -
Park Chosen for Principality of Monaco/ITER Postdoctoral Fellowship
(Jaesun Park in the Integrated Master's and Doctoral Degree Program )
Jaesun Park from the Department of Physics, was selected as a Principality of Monaco/ITER Postdoctoral Fellowship recipient.
This program was established by the Principality of Monaco and an international organization, ITER, in January 2008 to support postdoctoral researchers who will be working for ITER. It is a relatively competitive program because it chooses only five people every two years.
The selected postdoctoral researchers will be working for ITER for two years while conducting research projects with outstanding researchers in the field of nuclear fusion.
ITER, one of the most ambitious energy projects, was launched in 1985 with the purpose of carrying out joint research on nuclear fusion energy. Currently, about 800 people are working for this organization.
Seven ITER member countries (i.e. Korea, the European Union, the United States, China, Japan, Russia, and India) are sharing the expenses and engaging in mega-scale science projects. Korea shares 9.1% (20 billion Euro) of the total construction costs of ITER experimental devices.
Park will begin his duties in early 2019.
2018.05.04 View 7682 -
Professor Hee-Sung Park Named Scientist of May
(Professor Hee-Sung Park)
Professor Hee-Sung Park from the Department of Chemistry was named ‘Scientist of May’ sponsored by the Ministry of Science and ICT and the National Research Foundation of Korea. Professor Park was honored in recognition of his developing a tool to engineer designer proteins via diverse chemical modifications. This approach provides a novel platform for investigating numerous diseases such as cancer and dementia.
His research focuses on the production of synthetic proteins and the generation of diverse protein functions as well as the designing and engineering of new translation machinery for genetic code expansion, and the application of synthetic biology techniques for basic cell biology and applied medical science.
Post-translational modifications (PTMs) are constantly taking place during or after protein biosynthesis. PTMs play a vital role in expanding protein functional diversity and, as a result, critically affect numerous biological processes. Abnormal PTMs have been known to trigger various diseases including cancer and dementia. Therefore, this technology enables proteins to reproduce with specific modifications at selected residues and will significantly help establish experimental strategies to investigate fundamental biological mechanisms including the development of targeted cancer therapies.
Professor Park also received 10 million KRW in prize money.
2018.05.04 View 8210 -
Undergrad's Paper Chosen as the Cover Article in Soft Matter
(from left: Research Professor KyuHan Kim and Undergrad Student Subeen Kim)
A KAIST undergraduate student, Subeen Kim, had his paper chosen as the cover article in an international journal during his senior year.
There have been an increasing number of undergraduate students who were published as the first author because the KAIST Undergraduate Research Participation program allows more active research participation by undergraduate students.
Through URP, Kim successfully published his paper in the internationally-renowned journal, Soft Matter, which is published by the Royal Society of Chemistry, and it was chosen as the cover article of that journal in February 2018.
This publication means a lot to him because he designed the cover image himself, based on his imagination and observations.
His research is about controllable one-step double emulsion formation. Double emulsion is a system in which dispersed droplets contain additional immiscible liquid droplets.
Having great retention ability, double emulsion has been used in various applications in the food industry, in cosmetics, and for drug delivery. Nevertheless, two-step emulsification is a conventional approach to produce double emulsions that typically leads to partial destabilization of the emulsion formed during the initial stage. Hence, it does not ensure the stability of a double emulsion. On the other hand, a microfluidic approach with various flow-focusing techniques has been developed, but it has low production efficiency and thus limited industrial applications.
Kim’s results came from the process of phase inversion to solve this problem. He identified the instant formation of double emulsions during the process of phase inversion. Based on this finding, he proposed criteria to achieve high stability of double emulsion.
Through constant research, he developed a quite general method using a combination of an oil soluble poly methyl methacrylate (PMMA) and hydrophobic silica nanoparticle (HDK H18). This new method enables one-step and stable production of double emersions in a stable manner. It also allows control of the number and the volume of inner oil droplets inside the outer water droplets by adjusting PMMA and HDK H18.
Kim enrolled at KAIST as a KAIST Presidential Fellowship and Presidential Science Scholarship in 2014. While studying both chemical and biomolecular engineering and chemistry he has been developing his hypothesis and conducting research.
He was able to begin conducting research because he has taken part in URP projects twice. In his sophomore year, he studied the formation of high internal phase double emulsions. After one year, he conducted research to produce superabsorbent resins, which are the base material for diapers, by using colloid particles. Using partial research outcomes, he published his paper in Nature Communications as a second author.
Kim said, “Double majoring the chemical and biomolecular engineering and chemistry has helped me producing this outcome. I hope that this research contributes to commercializing double emulsions. I will continue to identify accurate principles to produce chemicals that can be controlled exquisitely.”
Figure 1. The cover article of Soft Matter
2018.05.03 View 9288 -
Cross-Generation Collaborative Labs Open
KAIST opened two cross-generation collaborative labs last month. This novel approach will pair up senior and junior faculty members for sustaining research and academic achievements even after the senior researcher retires.
This is one of the Vision 2031 innovation initiatives established to extend the spectrum of knowledge and research competitiveness. The selected labs will be funded for five years and the funding will be extended if necessary. KAIST will continue to select new labs every year.
A five-member selection committee including the Nobel Laureates Professor Klaus Von Klitzing at the Max-Planck Institute for Solid State Research and Dr. Kurt Wüthrich from ETH Zürich selected the first two labs with senior-junior pairs in March.
(Two renowned scholars' Cross-Generation Collaborative Labs which opened last month.
Distinguished Professor Lee's lab (above) andChair Professor Sung's lab)
Both labs are run by world-renowned scholars: the Systems Metabolic Engineering and Systems Healthcare Laboratory headed by Distinguished Professor Sang-Yup Lee in the Department of Chemical and Biomolecular Engineering and the Acousto-Microfluidics Research Center for Next-Generation Healthcare led by Chair Professor Hyung Jin Sung in the Department of Mechanical Engineering.
Distinguished Professor Lee will be teamed up with Professor Hyun Uk Kim, and their lab aims to mass produce new eco-friendly chemical materials as well as higher-value-added materials which will be used for medicine. The new platform technologies created in the lab are expected to provide information which will benefit human healthcare.
Meanwhile, the Acousto-Microfluidics Research Center for Next-Generation Healthcare will team up with Professors Hyoungsoo Kim and Yeunwoo Cho under Chair Professor Sung. The lab will conduct research on controlling fluids and objects exquisitely on a micro-nano scale by using high-frequency acoustic waves. The lab plans to develop a next-generation healthcare platform for customized diagnoses as well as disease treatment.
KAIST President Sung-Chul Shin, who introduced this novel idea in his research innovation initiative, said that he hopes the Cross-Generation Collaborative Labs will contribute to honoring senior scholars’ research legacies and passing knowledge down to junior researchers in order to further develop their academic achievements. He said, “I sincerely hope the labs will make numerous research breakthroughs in the very near future.”
2018.05.03 View 9910 -
Escalation of Competition Leads to Conflict in Competitive Networks of F1 Drivers
(Professor Wonjae Lee at the Graduate School of Culture Technology)
A new study has revealed that people with similar social status in similar age groups are more likely to clash with each other. This rivalry could likely lead to taking more risks in fair weather conditions.
Competition, while is often seen as beneficial, can escalate into destructive conflict. This occurs, for instance, when athletes sabotage each other or when rival executives get caught up in a career-derailing fight. These escalations, which lead to conflict, are especially likely among similar-status competitors, who are fraught with discordant understandings of who is superior to whom.
A research team of KAIST, the US Treasury, INSEAD, and the European School of Management and Technology (ESMT) examined the link between status similarity and conflict as well as the conditions under which this link holds by using panel data on Formula 1 races from 1970 through 2014. For the study, the research team analyzed a total of 506 collision cases by 355 F1 drivers over 45 years.
The team found that similar-status F1 drivers are more prone to collide, especially when they are age-similar, performing well, and feeling safe. When these boundary conditions are met, structural equivalence likely triggers antagonism among interactants.
This research deepens the understanding of when violent conflict emerges and when prevention efforts are called for. Professor Lee from the Graduate School of Culture Technology at KAIST said, “People are not sure about their identity when facing competitors of a similar status. People tend to confirm their own stature by beating an opponent.”
The team investigated the factors that escalate competition into dangerous conflict. Recently, sociological theorizing claims that such escalations are particularly likely in pairs of structurally equivalent actors who have the same relations with the same third parties. Using the F1 data, the research team modeled the probability that two drivers would collide on a racetrack as a function of their structural equivalence in a dynamic network of competitive relationships.
Professor Lee added, “We fully understand that the drivers who ranked first and second are likely to have more conflict because they meet more frequently and know each other well. We also regulated all those conditions and confirmed that our hypothesis worked right throughout the data analysis.”
Professor Lee, who wrote his doctoral thesis on tennis tournaments for identifying the ideal organizational structure, said that sports tournaments would be best optimized for comprehending the nature of organizational structures. Tournaments, even those with rankings based on objective criteria, are in fact intensely social. However, most prior empirical work in this area has relied only on official information on competitors’ performance, thus failing to capture the important elements of past competitive encounters.
“It is not so easy to obtain data on rivalries and conflicts inside an organization. However, in sports, the performances of athletes are all recorded and the data can be utilized as a very objective methodology for understanding social relations and their structural affects.
Official positions in tournaments, although clearly informative, can also be reductionist –excluding the emotionally salient features of competitors’ histories and forcing competitors together on a scalar metric, even when the competitors themselves do not see each other as comparable.
The results from sample-split models are important for social networking research, which has paid scant attention to the contextual conditions in which structural equivalence is most consequential for social action – especially hostile social actions.
The study suggests that new work will benefit from examining how demographic overlap, network stability, and perceived costs of conflict “activate” a structurally equivalent relationship to the point that it is not only salient but also conducive to conflict.
Professor Lee said, “Sociology mainly investigates the positive results of social success and collaboration. This study shows that any violent activities, including homicide, also have something to do with organizational and social structural equivalence.”
This study was co-led by Professor Matthew Bothner from ESMT in Germany, Professor Henning Piezunk from INSEAD in France, and Dr. Richard Haynes from the US Treasury and was featured at the PNAS (Proceedings of the National Academy of Sciences of the USA) in March.
(Figure: Drivers' competitive network and collisions. Nodes are drivers. Nodes enricled in black are labeled by name. Edges denote joint competition in at least one race. Red edges connecting indicate that the two drivers collided at least once. Using Fruchtermna-Reingold, nodes are generally proximte to the extendt that their average structural equivalence (over all races, from 1970 to 2014) is high.)
2018.04.24 View 6654 -
Professor Ju, to Receive Grants from HFSP
(Professor Young Seok Ju)
Professor Young Seok Ju from the Graduate School of Medical Science and Engineering was selected as a young investigator to receive research funds from the Human Frontiers Science Program.
The Human Frontiers Science Program (HFSP) was founded in 1989 with members of the G7 and European Union to stimulate innovative research in the field of life sciences.
Professor Ju placed third out of the eight teams that were selected from 158 applicants representing 60 countries. He is now the fourth Korean to receive a research grant as a young investigator. Professor Jae Kyoung Kim from the Department of Mathematical Sciences also received this prize last year, hence KAIST has produced grant recipients for two consecutive years.
Professor Ju is a medical doctor specializing in cancer genomics and computer biology. He has been studying somatic mutations and their functional consequences in human cancer in a bioinformatics way. He has published papers in international journals including Nature, Science, Genome Research, and Journal of Clinical Oncology.
With a title ‘Tracing AID/APOBEC- and MSI-mediated hyper-mutagenesis in the clonal evolution of gastric cancer,’ Professor Ju will receive 1.05 million dollars for three years along with Professor Bon-Kyoung Koo from the Institute of Molecular Biotechnology at Austrian Academy of Sciences, and Sinppert Hugo from University Medical Center Utrecht.
Professor Ju said, “As a young investigator, it is my great honor to receive this research fund from this organization. Through this internationally collaborative research, I will carry out groundbreaking research to understand the pathophysiology of cancers at a molecular level.”
2018.04.24 View 7262 -
Animal Cyborg: Behavioral Control by 'Toy' Craving Circuit
Children love to get toys from parents for their birthday present. This craving toward items also involves object hoarding disorders and shopping addiction. However, the biological meaning of why the brain pursues objects or items has remained unknown. Part of the answer may lie with a neural circuit in the hypothalamus associated with “object craving,” says neuroscientist Daesoo Kim from the Department of Biological Sciences at KAIST.
His research team found that some neurons in the hypothalamus are activated during playing with toys in mice. Thanks to optogenetics, they proved that these neurons in the hypothalamus actually governs obsessive behavior toward non-food objects in mice.
“When we stimulate a neuron in the hypothalamus of mice, they anxiously chased target objects. We found evidence that the neural circuits in the medial preoptic area (MPA) modulate “object craving,” the appetite for possessing objects” said Professor Kim.
Researchers also proved that the MPA circuit facilitate hunting behavior in response to crickets, a natural prey to mice, showing the role of this circuit for catching prey. Further, the MPA nerves send excitatory signals to the periaqueductal gray (PAG), located around the cerebral aqueduct, to create such behavior. The team named this circuit the ‘MPA-PAG’ circuit.
The team showed that they could control mammalian behavior for the first time with this scheme of MPA-Induced Drive Assisted Steering (MIDAS), in which a mouse chase the target objects in the front of head during stimulation of the MPA-PAG circuit. MIDAS allows mice to overcome obstacles to move in a desired path using optogenetics.
(Professor Daesoo Kim)
Professor Kim, who teamed up with Professor Phill Seung Lee in the Department of Mechanical Engineering, explained the significance of the research, “This study provides evidence to treat brain disorders such as compulsive hoarding and kleptomania. It also contributes to the development of technology to control the behavior of animals and humans using strong innate motivation, and thus could impact neuro-economics, defense, and disaster relief.”
He said the team would like to complete the neural circuit map governing behaviors of possession and hunting in the near future by exploring correlations with other neural behaviors controlling possessing and hunting activities.
This research was funded by the Samsung Science and Technology Foundation and published in Nature Neuroscience in March 2018.
(Figure 1: Schematics showing possessive behavior induced by the MPA neural circuit)
(Figure 2: Schematics of the MIDAS system that controls mammals behavior using the desire to possess. A MIDAS mouse is following the bait object controlled wirelessly.)
2018.04.23 View 8624 -
Deep Learning Predicts Drug-Drug and Drug-Food Interactions
A Korean research team from KAIST developed a computational framework, DeepDDI, that accurately predicts and generates 86 types of drug-drug and drug-food interactions as outputs of human-readable sentences, which allows in-depth understanding of the drug-drug and drug-food interactions.
Drug interactions, including drug-drug interactions (DDIs) and drug-food constituent interactions (DFIs), can trigger unexpected pharmacological effects, including adverse drug events (ADEs), with causal mechanisms often unknown. However, current prediction methods do not provide sufficient details beyond the chance of DDI occurrence, or require detailed drug information often unavailable for DDI prediction.
To tackle this problem, Dr. Jae Yong Ryu, Assistant Professor Hyun Uk Kim and Distinguished Professor Sang Yup Lee, all from the Department of Chemical and Biomolecular Engineering at Korea Advanced Institute of Science and Technology (KAIST), developed a computational framework, named DeepDDI, that accurately predicts 86 DDI types for a given drug pair. The research results were published online in Proceedings of the National Academy of Sciences of the United States of America (PNAS) on April 16, 2018, which is entitled “Deep learning improves prediction of drug-drug and drug-food interactions.”
DeepDDI takes structural information and names of two drugs in pair as inputs, and predicts relevant DDI types for the input drug pair. DeepDDI uses deep neural network to predict 86 DDI types with a mean accuracy of 92.4% using the DrugBank gold standard DDI dataset covering 192,284 DDIs contributed by 191,878 drug pairs. Very importantly, DDI types predicted by DeepDDI are generated in the form of human-readable sentences as outputs, which describe changes in pharmacological effects and/or the risk of ADEs as a result of the interaction between two drugs in pair. For example, DeepDDI output sentences describing potential interactions between oxycodone (opioid pain medication) and atazanavir (antiretroviral medication) were generated as follows: “The metabolism of Oxycodone can be decreased when combined with Atazanavir”; and “The risk or severity of adverse effects can be increased when Oxycodone is combined with Atazanavir”. By doing this, DeepDDI can provide more specific information on drug interactions beyond the occurrence chance of DDIs or ADEs typically reported to date.
DeepDDI was first used to predict DDI types of 2,329,561 drug pairs from all possible combinations of 2,159 approved drugs, from which DDI types of 487,632 drug pairs were newly predicted. Also, DeepDDI can be used to suggest which drug or food to avoid during medication in order to minimize the chance of adverse drug events or optimize the drug efficacy. To this end, DeepDDI was used to suggest potential causal mechanisms for the reported ADEs of 9,284 drug pairs, and also predict alternative drug candidates for 62,707 drug pairs having negative health effects to keep only the beneficial effects. Furthermore, DeepDDI was applied to 3,288,157 drug-food constituent pairs (2,159 approved drugs and 1,523 well-characterized food constituents) to predict DFIs. The effects of 256 food constituents on pharmacological effects of interacting drugs and bioactivities of 149 food constituents were also finally predicted. All these prediction results can be useful if an individual is taking medications for a specific (chronic) disease such as hypertension or diabetes mellitus type 2.
Distinguished Professor Sang Yup Lee said, “We have developed a platform technology DeepDDI that will allow precision medicine in the era of Fourth Industrial Revolution. DeepDDI can serve to provide important information on drug prescription and dietary suggestions while taking certain drugs to maximize health benefits and ultimately help maintain a healthy life in this aging society.”
Figure 1. Overall scheme of Deep DDDI and prediction of food constituents that reduce the in vivo concentration of approved drugs
2018.04.18 View 10354