Why talk about this topic? From the perspective of applied research, the key question is not whether we need interdisciplinary research (or transdisciplinarity, or holistic problem solving, or systems thinking, or however else we may call it). Rather it is about how all of us identify the problems that matter for us, how we can use tools and knowledge in such a way that we can thrive both as individuals and as a society in nature. The preparation process for the talk, the presentation, and the following discussions led me to think a lot about these questions.

Most of us would agree that the boundaries between disciplines are artificial. Each discipline offers its own set of valuable tools and models that allow us to understand ourselves, our relations, and the world better. A bigger picture of both the problems ahead and the solutions available to us brings better understanding.

How to get to the bigger picture? I do not know, though apparently curiosity, exploration, time, good teachers, and a safe and supportive environment help. My family, friends, teachers, and mentors have encouraged me to think critically, work with creativity, and collaborate with others whenever possible, which seem to be essential steps towards the bigger picture, too. Even when I do not always manage to be critical, creative, or collaborative, it has brought me bliss to improvise and to move toward these goals whenever possible. The visceral experience inspired me to share my limited experience with the teachers at the Gymnasium Muttenz.

As a highlight of the event, about 100 teachers wrote down why they decided to teach the subject they are specialized in. I read each reply and was deeply touched by many of them. One teacher recalled her love of Italian football, which motivated her to teach the Italian language. Another simply wrote ‘I appreciate the beauty of physics’ - exactly what most physicist friends told me - ‘and want to pass it on’. A particularly beautiful reply came from a teacher who believes that everyone has two homes - her body and the earth - and that her subjects (geography and biology, or sport?) help students to maintain the health of both. Many colleagues appreciated the opportunity to re-immerse in the excitement, joy, and love for their subjects, probably first felt long before they became experts. In addition, it was visibly fun to share the passion with their peers.

I thank Andrea Seehuber and her colleagues for organizing the event and for inviting me, and all teachers who shared their personal experience and valuable feedback with me.

In the AMIDD course, we learn about the drug discovery process, and how mathematics and computer science contribute to the end-to-end process. The course is highly interdisciplinary: Over the years, students in mathematics, computer science, physics, biology, chemistry, medicine, and other disciplines have joined the courses, and given feedback to the curriculum so that it is accessible and understandable for participants of different background.

Information of the course and all materials can be found on http://amidd.ch. More information on the course can be found at the course directory of the University Basel. And if you want to get an impression of the course, the archived page of the 2024 semester may be of help.

For the fourth time in a row, we shall host ~12 PhD students enrolled in Swiss universities, and students from EU and UK universities if remaining positions are available. The applicants are expected to bring experience in data analysis and modelling (for instance statistical modeling, machine learning and artificial intelligence, mechanistic modeling, or causal inference), as well as enthusiasm in applying the skills to solve real-world problems in drug discovery. Together we shall address real-world problems in drug discovery and development.

To find out more about the summer school and to register, please visit our website at https://bedapub.github.io/PMDA-Summer-School.

All essential information is also included in this one-pager PDF file, which can be shared, printed, and posted anywhere.

Welcome to join us, and thank you for spreading the words!

The talk is motivated by two observations. First, target selection and modality selection in drug discovery have a invisibly high potential cost, and remains challenging despite great progress in biology, chemistry, and computational sciences including machine learning and artificially intelligence. Second, protein turnover, i.e. the constant synthesis and degradation of proteins, affects efficacy, potency, ADME (absorption, distribution, metabolism, and excretion) properties, and safety of drug candidates. Critically, I believe the impact of turnover on target and modality selection is currently under-appreciated, and the intrinsic link between target biology such as turnover and a drug’s efficacy and safety supports the oneness of target and modality selection.

In a review that my colleagues and I am writing, which is currently under revision, we try to illustrate why we believe that protein turnover is essential for target prioritization and modality selection, especially for emerging modalities such as covalent inhibitors and targeted protein degraders. There are still many open questions that I wish can be addressed by the community by working together.

My talk at ETH gives a glimpse of some of our thoughts, and invites both criticism and collaboration. It is built upon another talk, Defining Human Dosing for Covalent Inhibitors with Translational PK/PD and Protein Turnover Data, which I co-presented with my mentor, Neil John Parrott, in a recent DMDG meeting Focusing on Targeted Covalent Drugs: how to best identify and develop TCIs. DMDG is an informal world-wide association for scientists engaged in research and development within the drug metabolism, pharmacokinetics and related disciplines of the pharmaceutical industry.

It was a great visit, packed with the talk and many interesting discussions. I thank Prof. Beltrao and Manuela Brunner-Markl, the administrative assistant of the institute, for organizing the day.

The slides of my talk are distributed with the GPL-3 license. If you have questions, suggestions, criticism, and questions, please feel free to reach out to me.

A major part of my PhD work was about inferring functions of microRNA, studying how microRNA regulates gene expression in diseases including breast cancer, and using microRNA as diagnostic tools.

Together with my colleagues, we discovered that two very similar clusters of microRNAs, miR-200bc/429 and miR-200a/141, have distinct effects on proliferation and invasion of breast cancer cells. Later studies further revealed that these miRNAs are up-regulated in human breast tumors compared with normal tissues. Interestingly, in most aggressive molecular subtypes including Luminal B, HER2 and triple negative, their expression is again reduced. These subtypes are featured with increased epithelial-to-mesenchymal transition (EMT) and metastasis. Whether the lower expression of miR-200 miRNAs is causal, for instance whether restoring their expression would reduce the risk of metastasis, is to my best knowledge inconclusive.

A landmark discovery by Ambros and Ruvkun was that microRNAs, often being promiscuous regulators of many proteins, are themselves tightly regulated during developmental phases, for instance in the nematode worm Caenorhabditis elegans (C. elegans). It seems that such phase-specific expression patterns also apply to tumor development.

Motivated by our initial work with microRNAs, my colleague and mentor Özgür Sahin designed and performed a miRome-wide proteomics screening, where we over-expressed one human microRNA a time and measured how two dozens of proteins change their expression in breast cancer cells. Our work become one of the first studies that describe the network of miRNA-protein regulation at the global level. By developing and applying a new network-analysis methodology, we detected consistent and intrinsic regulatory patterns where miRNAs simultaneously co-regulate several proteins that act in the same functional module. While it was already known to the field that miRNAs with similar sequences often target a same set of proteins, our observation further suggested that even dissimilar miRNAs cooperate to target proteins of similar functions, thereby reinforcing the effect of each other. It’s like pointing several guns against a gang of several criminals: the co-regulation makes it more likely that the cell is ‘locked-in’ in a state.

Do miRNAs, like siRNAs (small interference RNAs), have the potential to become drugs? The News and View article associated with our study, authored by Marcos Malumbres and titled miRNAs versus oncogenes: the power of social networking, published in 2012, made the interesting observation the fact that AKT1 and ERK2, two major kinases in the PI3K and RAS oncogenic pathways, may be co-downregulated by 30 miRNAs suggests that targeting miRNAs (including targeting pairs of them) may become new therapeutics. In 2017, Rupaimoole and Slack reviewed development of miRNA-based therapeutics, particularly in oncology, and reported that several therapeutics have already advanced into clinical testing. However, a review by Kim and Croce in 2023, notes that until then no miRNA-based therapies have been approved. This is a stark contrast to siRNA (for which Andrew Z. Fire and Craig C. Mello were awarded the Nobel Prize in Physiology or Medicine 2006), which has made into several drugs including Patisiran and givosiran. Zhang et al., 2021 argues that this is probably due to the fact that one miRNA generally targets tens or hundreds of genes. The too-many-targets-for-miRNA-effect, according to the author, poses a higher hurdle with regard to safety.

How does it look in the pipelines now? A quick check on ClinicalTrials revealed two ongoing, recruiting Phase I-II trials using microRNAs as therapeutics: AMT-162, an artificial microRNA targeting the SOD1 gene for SOD1 amyotrophic lateral sclerosis (Phase 1/2); and ATX-01, an anti-miR that inhibitors the microRNA miR-23b (Phase 1/2a). I am excited to learn the outcome of these and other finished trials.

I feel a bit shamed to confess that I did not know the names of Victor Ambros and Gary Ruvkun before, despite the fact that I worked with miRNAs for many years. From the scientific background provided by the Nobel prize committee, I could recognize the name of David Bartel (whose lab developed the much appreciated database of miRNAs and their targets, known as TargetScan. Though I was familiar with the stories that miRNA was first identified from C. elegans, by reading the press release and the scientific background, I learned about the amazing story of how Ambros and Ruvkun connected with each other and recognized the complematarity of sequences of the first-discovered miRNA, lin-4, and the protein-encoding mRNA, lin-14.

The discoveries made by Ambros, Ruvkun, and many other pioneers of microRNA biology revealed that by base-pair matching mechanism, microRNA binds to untranslated regions at the 3’-end of mRNA (3’-UTR). Starting from there, many researchers, most but few names of which remain unfortunately unknown to me, have built a huge branch of knowledge about how microRNAs expand and function during evolution, and how they are regulated in development and disease. The short, sometimes partial, yet always elegant matching of 21-23 nucleotides between miRNAs and mRNAs keeps fascinating me, after so many years.

For the third time in a row, we shall host ~12 PhD students enrolled in Swiss Universities. The applicants are expected to bring experience in data analysis and modelling (for instance statistical modeling, machine learning and artificial intelligence, mechanistic modeling, or causal inference), as well as enthusiasm in applying the skills to solve real-world problems in drug discovery. Together we shall address real-world problems in drug discovery and development.

To find out more about the summer school and to register, please visit our website at https://bedapub.github.io/PMDA-Summer-School.

All essential information is also included in this one-pager PDF file, which can be shared, printed, and posted anywhere.

Welcome to join us, and thank you for spreading the words!

We shall simulate a clinical trial, analyse the data, and interpret the results together with a Jupyter notebook.

The source code of the fun project is available in a GitHub repo. And the essential information about the workshop is included in this one-pager PDF file (German), which can be shared and printed anywhere.

I want to thank Ralf Horstmoeller, Marie Pachtova, Paul Geser, David Gaul, Giulia Ferraina, and Jannick Lippuner for their support.

Following last year’s success of the 1st Roche PMDA Summer School, we shall again open our door to PhD and outstanding master students enrolled in University Basel, ETH D-BSSE, and other Swiss Universities. To find out more about the summer school and to register, please visit our website at https://bedapub.github.io/PMDA-Summer-School.

All essential information is also included in this one-pager PDF file, which can be shared, printed, and posted anywhere.

Welcome to join us, and thank you for spreading the words!

In this international event, the organizers expect around 70 participants. The event seeks to bridge bioinformatics and clinical research and have exciting talks, panel discussions and a poster session.

Registration is free of charge and participants are selected upon submitting an abstract. The submission site can be found here. Abstract submission deadline is July 17th, 2023.

Please find the flyer of the event. More information cab be obtained from the event’s website. Have fun with submission!

The course series is organized by my colleague Adrian Roth, who is an expert of drug safety and new alternative methods. The course is attended mostly by master students of the Pharmacy Department of the University Basel. I have so far very good experience with the course: it covers a broad range of topics in drug discovery, it is given by a panel of experts working in diverse functions and assuming varying roles, the lecture is well organized by Adrian and her assistant Mrs Christiane Kocher, and probably the most important of all, the students are curious and engaged.

This semester, my talk will be about my current understanding of multiscale modeling of drug pharmacology and safety. My hope is to introduce three types of techniques that we often use to build computational models, namely mechanistic models, statistical models, and causal models. Together with in vitro, ex vivo, in vivo models, these modelling techniques give us the opportunity to understand how human body and drug interacts.

The key messages I tried to deliver are:

1. In drug discovery, we are often interested in multiple levels of working mechanism - molecular, cellular/omics, and system/organ-level - of drug candidates, with the final goal to achieve acceptable benefit/risk ratio in as large a population as possible.
2. Computational biologists in drug discovery build and use mechanistic, statistic, and causal models to achieve these goals.
3. Integrating data and models inform both disease understanding and drug discovery.

Here are the slides that I used for the lecture: slide deck. If you have comments, suggestions, and criticisms, please kindly let me know!