The drug discovery pipeline is used to describe the stages in drug discovery. The earliest stage concerns with the identification of potential targets and molecules ('hits') that can modulate their function, while more advanced stages are about developing these hits into viable experimental drugs and…

The Data-Driven Drug Discovery Network (D4N) is an initiative by researchers from Leiden University and collaborators to join efforts in applying and developing novel techniques from data science to drug discovery and related topics from bioinformatics.

How are new drugs developed? This question is central to the Minor Modern Drug Discovery (MDD), which covers the entire trajectory from disease to drug molecule and vice versa. The various research groups involved offer a complementary and interdisciplinary perspective by connecting the diverse subjects…

In the research programme Drug Discovery & Safety, we are interested in the efficacy and safety of new drugs and novel means to decipher these aspects. Hence, we employ advanced imaging and high-throughput screening techniques next to computational approaches such as chem- and bioinformatics.

Research in this group, headed by Gerard van Westen, focusses on computational methods integrated in different parts of the drug discovery process. More specifically, topics include innovative treatments for cancer, selectivity modeling, translational research, allosteric modulation, drug resistance…

We focus on a better understanding of the mechanisms of cancer drug resistance and metastasis.

In this research group, headed by Prof. Erik Danen, the aim is to unravel cellular signaling mechanisms in normal and diseased cells, with a long-standing interest in cell adhesion signaling. In complex multicellular organisms such as ourselves, a division of labor emerges where different tissues and…

The master's specialisation Drug Discovery and Safety at Leiden University provides students with research-oriented education into the discovery of new drug targets and new lead molecules, particularly in the field of cancer, through a combination of advanced imaging techniques (‘systems microscopy’),…

Despite recent advances in medicine, many devastating disorders like cancer and cardiovascular, neurodegenerative and infectious diseases still lack effective treatments. In order to address this challenge, we, as scientists from Leiden University, joined hands in the LED3 network. LED3, for Leiden…

To get a feeling of how we operate at LED3 when it comes to Early Drug Discovery, please browse through our case studies. When you select a case study you’ll find relevant contacts.

We cover the entire spectrum from target identification to the evaluation of the efficacy and safety of novel medicines in clinical practice.

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Supervisor: Indira Nederpelt

Discovery of metastasis promoting candidate drug targets

In the last decades, activity-based protein profiling (ABPP) has emerged as a powerful chemical tool that may aid the ever-challenging drug discovery process.

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Source: ChemMedChem (2015)

Heart failure is a major health care problem with high mortality.

Data analysis with Python and R are rapidly becoming essential skills for modern scientists. Therefore, we are offering courses to develop your scientific computing skills. Those courses are optional for LACDR PhD candidates.

This thesis describes the importance of being able to control the selectivity of potential drug candidates.

Activity-based protein profiling (ABPP, also termed chemical proteomics), is one of the pillars of chemical biology, and at LED3 we have taken it to the next level. ABPP allows the assessment of protein function in live cells and tissues, which means that the activity of a complete protein family can…

Establishing human induced pluripotent stem cell (iPSC) CRISPR-Cas9-based fluorescent reporter cell lines for NF-kB signalling. We will use this to enable studying the dynamic activation and downstream signalling of Toll-like receptor and cytokine signalling in iPSC-derived differentiated cells in a…

Drug-target binding kinetics determine the time course of the central event in pharmacotherapy: Drug-target interaction.

The goal of hit discovery is to identify suitable chemical starting points to modulate a drug target. A hit can be, a.o., a small molecule, a protein or mRNA. Hit identification is performed via rational design, genome mining, (targeted) library screening, or in silico approaches.

The goal of target discovery is to identify and validate proteins and biological pathways that are involved in the disease process. Modulating these target proteins and pathways with small molecules, therapeutic proteins or other biomolecules (e.g. mRNA) could deliver an effective and safe drug or v…

Promotor: A.P.IJzerman Co-promotor: A. Bender

Global healthcare is on the verge of an antibiotic availability crisis as bacteria have evolved resistance to nearly all known antibacterials. Identifying new antibiotics that operate via novel modes-of-action is therefore of high priority.

Can drugs that target host signaling pathways be used to eradicate antibiotic-resistant bacteria?

From nanoparticles to colliding ice planets and from biological origami to new x-ray scanner techniques: this year again, our scientists have made wonderful discoveries. From the largest numbers to the smallest molecules and from the oldest galaxies up to the latest algorithms, take a look at each institute's…

The main aim of this thesis was to unravel the signaling and regulatory networks that drive tumor cell migration during breast cancer metastasis.

Drug-related homicide (DRH) has the potential to act as a valuable indicator of wider drug-related crime. Yet DRH remains a knowledge gap within this broader field of study.

Supervisor: Lizi Xia

Can a new proteomics workflow be developed to link genes and gene clusters to bioactive molecules, identify novel compounds and enhance the production in the Streptomyces lividans enzyme?

This thesis focuses on data found in the field of computational drug discovery. New insight can be obtained by applying machine learning in various ways and in a variety of domains. Two studies delved into the application of proteochemometrics (PCM), a machine learning technique that can be used to…

The research within the Division of Cell Systems and Drug Safety, headed by Prof. Bob van de Water, is focused on novel therapeutic modalities and novel concepts in early drug discovery, in order to develop more effective and safer therapeutic strategies. We generate advanced cell and computational…

Improving healthcare with our scientific discoveries: that is the goal of pharmaceutical research at Leiden University. And there’s a lot involved in that. Our research starts with the discovery of the effect achieved by a particular substance, and sometimes continues all the way through to the development…

There are many complex links in the chain that provides patients with new drugs: from fundamental science, to clinical tests, to production. The entire chain can be found in Leiden. Leiden University, the Leiden University Medical Center (LUMC) and the businesses at the Leiden Bio Science Park (LBSP)…

During the course of drug discovery translational steps are made.

The Leiden Academic Centre for Drug Research (LACDR) is a centre of excellence for multidisciplinary research on drug discovery and development.

In the Drug Research theme, we primarily work with rodents. Rodents, such as mice, are one of the most common laboratory animals. These small mammals are easily housed and exhibit a rapid rate of reproduction.

From the Big Bang to superconductivity. Many ground-breaking discoveries have been made in Leiden University’s long history.

Drug development is a complex process in which many parties work together. Every day, the researchers at LACDR devote their energies to developing drugs that are new, better, more efficient and easier to produce. And thus to the millions of patients who know all too well why this research in Leiden…

High-throughput holistic preclinical screens are increasingly used in drug discovery, to assess both drug efficacy and drug safety.

The disease acute myeloid leukemia (AML) is characterized by fast progression and low survival rates.

Over several decades, a variety of computational methods for drug discovery have been proposed and applied in practice. With the accumulation of data and the development of machine learning methods, computational drug design methods have gradually shifted to a new paradigm, i.e. deep learning methods…

Is is possible to better predict the validity of drug candidates?