We cannot believe how quickly time has passed. CCADD students have finished the 15-week 'Clinical Pharmacokinetics and Pharmacodynamics in Drug Development' course with no leftovers or dropouts. The students have learned in details how the core principles and concepts of pharmacokinetics and pharmacodynamics could be applied to speed up clinical drug development and to increase its efficiency, particularly for anti-cancer drugs. In the class, students have not only thoroughly reviewed two textbooks ('Pharmacokinetics in Drug Development, Volume 3 and 4') from chapter to chapter, but also studied other literature, which could go up to tens of published papers. Tae, one of the students who took the course, said, "It was eye-opening to see how what we studied in clinical pharmacokinetics and pharmacodynamics has been used to real world drug development." He added, "The class was also full of fun. It was an opportunity for the CCADD students to know each other better."

This course was taught in English. That means all the student presentations were given in English!

Prof. Howard Lee proposed health insurance reimbursement for the combination therapy of DPP4 inhibitors and SGLT2 inhibitors, irrespective of their labels as approved by the Korea Ministry Food and Drug Safety (MFDS), at a special session organized by the Korean Diabetes Association (KDA), in association with its Spring Conference 2019, held on May 9-11, 2019, at the HICO, Kyeongju, Korea. Unlike other countries including the USA, EU, and Japan, MFDS in Korea has approved the combination therapy of SGLT2 inhibitors with other oral hypoglycemic agents, particularly with DPP4 inhibitors, only on the basis individual drugs, not on the therapeutic class. This unique regulatory approval has contributed to the delayed reimbursement of various combination therapies involving SGLT2 inhibitors since their approvals. 

The delayed reimbursement has caused a lot of debates not only between the pharmaceutical industry and the Health Insurance Review and Assessment Service or HIRA, but also among clinicians. With this background, the KDA asked Prof. Lee to share his perspectives from the points of drug regulatory science if the reimbursement for the combination therapy of DPP4 inhibitors and SGLT2 inhibitors on the basis of therapeutic class, not on the individual drug, has any scientific and clinical rationale. Prof. Lee, based on an intensive systematic literature review focusing on the pharmacokinetics, drug-drug interactions, clinical efficacy, and safety profiles of the combination treatment with DPP4 inhibitors and SGLT2 inhibitors, discussed that it is highly unlikely any combination of the two classes would interact in a clinically meaningful and significant way. Furthermore, Prof. Lee argued that it is very likely for every combination of a DPP4 inhibitor with an SGLT2 inhibitor to result in an additional, significant, and clinically meaningful decrease in HbA1c or glycated hemoglobin. However, since not every combination has been studied for its safety profiles although it is likely to be similar to those of monotherapy, Prof. Lee proposed to perform a real world data study under the auspice of KDA, sponsored by the pharmaceutical industry, to explore and confirm the safety and efficacy profiles of the combination therapy.      

Reflecting the interest in the reimbursement issue, the conference room was full of clinicians, industry representative, and journalists even though the session was presented early in the morning on Saturday. More detailed information on the session can be found here. 

On December 20, 2018, CCADD had a day-long workshop at the Yeongeon Campus. The workshop was attended not only by the existing CCADD members, but also by a new CCADD intern and a graduate student in the Interdisciplinary Program of Clinical Pharmacology at Seoul National University. The workshop included 12 presentations, the theme of which covered the history and milestones of CCADD, educational and research activities, talent acquiring strategy, homepage management, student internship experiences, communication, and teambuilding exercise. Furthermore, Professor Kyung-Sang Yu from the SNU College of Medicine and SNU Hospital (Department of Clinical Pharmacology) was invited to a special lecture session. Prof. Yu talked about the importance of e-mail as a means of business communication. He also stressed the appropriate e-mail manners in various business communication contexts.

After the workshop, CCADD members and their family members or invited friends went on a year-end dinner party, which was extended to a sleepover program. All brought a so-called 'useless' gift to the party, which as real fun. The winner of the most useless gift was Tae Chung, who received a used book named 'Sleep 2', written by Bernard Werber, but without having its first book, i.e., 'Sleep1'.

Okay, let's now look at the pictures below and you will easily notice how crazy the party was!

Prof. Howard Lee and Yoomin Jeon attended the 2018 Conference on Empirical Methods in Natural Language Processing (EMNLP 2018) held at the Square Meeting Center in Brussels from October 31^st through November 4^th, 2018. EMNLP is one of the top-tier conferences in the area of natural language processing organized by SIGDAT, the Association for Computational Linguistics (ACL) special interest group on linguistic data and corpus-based approaches to NLP. With the current artificial intelligence and machine learning boom from a variety of disciplines, this year's conference had a record-breaking number of submissions (2,231) and 2,500+ attendees, a 48% increase compared with EMNLP 2017. Of all the long and short papers submitted, only 549 papers were accepted, which can be found in the EMNLP proceedings. The conference included two days of workshops, followed by three days of main conference sessions including long and short presentations, tutorials, and demos. Researchers and practitioners from around the world gathered to share their latest research findings and emerging trends in machine learning for NLP, machine translation, language models, text mining, information extraction, and many more. 

In the 'Writing Code for NLP Research' tutorial, researchers from Allen AI Institute shared their best practices learned from designing the development of the Allen NLP toolkit, a PyTorch-based open-source library for deep learning NLP research. It was an excellent tutorial to learn practical advice on writing research code and to recognize the importance of having good quality codes. In the 'Deep Latent Variable Models of Natural Language' tutorial, deep latent variable models were covered, which are emerging as a useful tool in NLP applications. Mainly, three types of latent variable models (discrete, continuous, and structured) and inference strategies (exact gradient, sampling, and conjugacy) over the latent variables were examined. 

There were a number of presentations/papers in the clinical domain. One of the interesting papers, titled 'emrQA: A Large Corpus for Question Answering on Electronic Medical Records', proposed a novel semi-automated framework to generate domain-specific large-scale question answering (QA) corpus by leveraging expert annotations on clinical notes for various NLP tasks from the i2b2 challenge datasets. For medical QA on EMR, they released 400K+ question-answer evidence pairs and 1M question-logical forms, a representation useful for generating corpus. Generating patient-specific QA from an EMR is an important NLP task to process a natural language question and provide a human level accuracy answer. Among many datasets that were presented at the conference, a clinical domain dataset MedNLI was included. MedNLI is a Natural Language Inference (NLI) dataset on the medical history of patients annotated by physicians, which we can later refer in our research.   

Five CCADD members (Prof. Howard Lee, Dr. Soohyun Kim, Yoomin Jeon, Tae Chung, Serin Lee) have attended the Fall conference of The Korean Society of Medical Informatics (KOSMI) held at Chonbuk National University on November 22-23, 2018. The theme of the conference was 'Real World Data to optimize clinical trials', which reflects a growing role and value of big data and artificial intelligence for clinical trials. Over 700 people from academia, public institutions, and the pharmaceutical industry gathered to share their experiences, practices, insights, and perspectives on the more active use of data and information sciences in clinical trials.

Prof. Howard Lee spoke about AI-based patient recruitment in clinical trial in an invited session, entitled 'A Dimensionality Reduction Model to increase the Efficiency and Accuracy of Clinical Trial Feasibility Assessment using Electronic Medical Records(EMR)'. Prof. Lee emphasized the application of AI technology to clinical trial feasibility such as feature selection algorithms in machine learning to identify common sensitive eligibility features (cSEFs). 

Yoomin Jeon and Tae Chung presented a poster at the conference too. Yoomin's poster was about the actual application of what Prof. Lee introduced in his talk. Tae examined the extent of mapping of ICD-10 to MeSH to crosswalk and synchronize different terms collected from different data sources. (Analysis of agreement status between the diagnostic code of MeSH and ICD-10).

Meanwhile, Dr. Soohyun Kim led a tutorial session, where she taught several essential statistical methods for biomedical informatics research using R. 

For more details, you may want to contact Yoomin Jeon or Tae Chung.

Prof. Howard Lee has been recently awarded a government grant from the Small Grant Exploratory Research (SGER) Program through the National Research Foundation of Korea or NRF to develop a model for assessing clinical trials feasibility. The total research funding was $223,000 over a 3 year period (11/01/18 to 10/31/21), which is equivalent to 250 million Korean Won. After a year of an initial stage of research, funding may be continued for additional two more years based on satisfactory progress. The title of Prof. Lee's proposed research plan was "A Dimensionality Reduction Model to increase the efficiency and accuracy of clinical trial feasibility assessment using electronic medical records". This research aimed to develop a machine learning-based dimensionality reduction model to identify the common sensitive eligibility features (cSEFs) that could increase the efficiency of clinical trials feasibility in the presence of intended patient population characteristics. Feature Selection algorithms will be used to enhance the performance of this machine learning model. 

Prof. Howard Lee emphasized the importance of the holistic approach to ensure the safe use of biological agents, particularly in the field of rheumatology, at a policy forum sponsored by the Korean College of Rheumatology, held at the Seoul Foreign Correspondents' Club, Press Center, on November 14, 2018. Biological agents, since first introduced in the late 1990s, have changed the way that physicians managed patients with various connective tissue diseases, of which rheumatoid arthritis is a typical example. "Because biological agents are way different from small-molecule drugs in terms of their safety profiles, which most physicians are not familiar with", Prof. Lee said, "they have to be used carefully, preferably only by those who were trained how to correctly prescribe them and those who are experienced in detecting the adverse reactions, which often clinically manifested in atypical forms." "Reactivation of latent tuberculosis and increased occurrence of opportunistic infections are some examples", Prof. Lee added. Registries of patients using biological agents can be a useful tool to track down and detect adverse effects of biological agents, which are not easy to be screened out in clinical trials before marketing approval. In that sense, Prof. Lee requested the rheumatology society to be more proactive by initiating and maintaining a series of safety measures, hopefully under a full collaboration with and support by the regulatory agency. Most of the panelists at the forum agreed with Prof. Lee. 

Two CCADD members, Dr. Soohyun Kim (PhD in statistics) and Siun Kim (BS in biology) gave presentations at the 2018 Korean Statistical Society Fall Conference , held on November 2-3 at Ewha Womans University, Seoul, South Korea. Dr. Kim gave an oral presentation of an update of her research on optimal experimental design. Additionally, Siun presented a poster discussing the appropriateness of an equivalence margin used in a clinical trial with CT-P13, an infliximab biosimilar, developed by Celltrion. Dr. Kim’s presentation was well received from her peer statisticians, who have been actively working in the field of experimental statistics in Korea. Interestingly, statisticians at Celltrion dropped by Siun’s poster and asked several questions. On the first day of the conference, Dr. Kim joined a tutorial session on deep learning from a statistician’s point of view.