The aim of this research area is to be able to predict human drug response on the basis of mathematical models that are developed using preclinical experiments and prior knowledge.

In the future, physicians may be able to identify dementia much earlier than they can today because a computer algorithm will be able to predict from brain scans how our memory is going to develop.

Prof. Elizabeth de Lange is concerned with the allocation of resources for the conduct of science towards the goal of best serving the public interest. Also, while she underscores that there is still the need for using animals in drug research, she is concerned about this use, and advocates the use…

Supervisor: Gerard van Westen

Alternatives to current practice

Less than 1 in 10 drug candidates that enter phase 1 clinical trials actually gets approved for human use.

ASLU 14

A research agenda

Research goal: To support the design of technologies (counter-measures and communication measures) for the prevention, interdiction and mitigation of lone actor extremist events (LOEEs), which are hard to anticipate, yet can be highly damaging to local and national communities and therefore must be…

How to come to valid risk stratification of alcohol use disorder?

Promotores: Prof.dr. M. Danhof, Prof.dr. D.R. Stanski

A new research line is the development of liquid biopsy fingerprints to predict early Alzheimer’s disease (AD) stage in human in readily accessible body fluids in human (in collaboration with: Dr. Geert-Jan Groeneveld, CHDR; Prof. Elga de Vries, Free University Medical Center; and others).

Promotor: P.D. Grünwald

Promotor: Prof.dr. M. Danhof, Co-promotor: O.E. Della Pasqua

An integrated approach of physiological concepts, advanced statistical approaches and large clinical datasets.

Are predictive archaeological maps a reliable tool to play an important role in the spatial planning? One of the goals of this project was to develop best practices for the production and application of the models.

Source: Nature Biotechnology, Volume 2014, Issue June (2014)

Clinical development of drugs for central nervous system (CNS) disorders has been particularly challenging and still suffers from high attrition rates.

This thesis consists of five chapters on how to construct prediction sets for different types of data and models in a parametric or nonparametric Bayesian paradigm.

Prediction of human (CNS) target site concentrations in health and disease In the vision of Prof. de Lange we will only be able to predict human (central nervous system, CNS) target site concentrations and effects if we perform systematic, condition-dependent, integrative, and strictly quantitative…

Source: J Cheminform, Volume 7, Issue 1 (2015)

Source: Nat Biotechnol, Volume 32, Issue 12, pp. 1213-22 (2014)

Describe and identify what dosimetry parameters are of importance to interpret dose-response relationships (eg., mortality, sub-lethal, growth or reproduction inhabitation, DNA damage and reactive oxygen species, etc. ) for metal-based nanoparticles? How to develop quantitative models that enable to…

Can we tailor catalysts at the atomic scale by means of high-school chemistry and geometry rules?

The lack of success of new CNS drugs in clinical development is in part due to the complexity of the CNS, unexpected side effects, difficulties for drugs to penetrate the brain, but also by the lack of biomarkers.

Can a newly developed, app-based, personalized maintenance program enhance the effectiveness of the exposure-based one-session-treatment for children with a specific phobia?

A novel mathematical model describes spatial-temporal drug distribution within one or more brain units, which are cubic representations of a piece of brain tissue with brain capillaries at the edges.

Although many studies have addressed democracy in education around the world, so far research on democratic education in the context of communist society has been scarce. In the current study, we aim to clarify the concept of democratic value and its manifestation in Vietnam’s schools. In addition,…

Clearance is the most important pharmacokinetic parameter for drug dose selection. Pharmacokinetic information is typically first available in the adult population, and in general only limited pharmacokinetic data are available in children when drugs enter into the market. It is therefore of the utmost…

The kidneys play a major role in the elimination of drugs. In children, the exact age-related physiological changes underlying kidney function remain largely unknown.

Cláudio de Sá predicted the preferences of people using rankings. He adjusted ‘classical’ machine learning approaches, making them suitable for predicting preferences. His work can be applied in the prediction of election results. PhD defence on 16 December.

Promotores: Prof.dr. C.A.J. Knibbe, Prof.dr. M. Danhof, Prof.dr. K. Allegaert (Leuven)

Heavy rainfall can cause streets to flood and basements and tunnels to overflow. Jan van Rijn investigated, together with Christiaan Lamers (formerly of Leiden University) and Ton Beenen (STOWA, RIONED), how data science can help to predict which areas are at greater risk of flooding. Van Rijn presented…

It is a stormy Sunday afternoon, with gusts of a whopping 110 kilometres per hour. Chemist Teun Sweere defies the enormous headwind on his city bike and wins the NK Headwind cycling after 22,5 minutes. A new highlight follows six months later: his PhD defence (14 June).

An indian stepwell on a nanoscale. That is what postdoc Nakkiran Arulmozhi calls the pattern he saw when he corroded a special kind of platinum crystal. The unique images show the destructiveness of the process, but also show how predictable it is.

There is a link in adolescents between brain connections and impulsiveness. Leiden researchers have discovered that these connections also predict which adolescents will make more impulsive choices two years further on.

Promotor: Prof.dr. M. Danhof, Co-promotor: E.C.M. de Lange

As of 1 March 2018, Elizabeth (Liesbeth) de Lange has been appointed as Professor of Predictive pharmacology at the Leiden Academic Centre for Drug Research (LACDR). She is head of the research group Predictive Pharmacology and mainly aims at developing mathematical models that can predict the effect…

With the use of big data, Leiden University is aiming to develop a system that sends automatic alerts when certain Industrial parts are starting to wear out. Researchers of the the Leiden Institute of Advanced Computer Science (LIACS) are developing a predictive maintenance platform together with, among…

Predicting cancer survival with machine learning, that is the aim of a new collaboration between the Mathematical Institute, the European Organisation for Research and Treatment of Cancer (EORTC) in Brussels and Leiden University Medical Center. The focus of this project is to characterise the model…

Does a drug enter into the human brain once administered in the body?

The main objective of this thesis was to develop clinically relevant survival models for patients with high-grade soft tissue sarcoma of the extremities, in particular the development and validation of prediction models for use in clinical practice.

The DASPO-group for data analysis and survival in personalized sarcoma at the Mathematical Institute has developed an app that provides personalised predictions for patients suffering from soft tissue sarcomas. Due to the aggressive nature of such tumors, the prognosis for such patients is poor, even…

A new study in Nature Plants has explored the most important organising principles that control vegetation behaviour. The insights from this study can be used to improve predictions on climate change. Leiden scientists Peter van Bodegom and Nadia Soudzilovskaia participated in the study.

To what extent does human intervention influence the world’s biodiversity? And can we predict how biodiversity and ecosystems will change in the coming years? Inaugural lecture by Peter van Bodegom, Professor of Conservation Biology, on 8 May.

Stars orbit black holes while jumping up and down. This is the prediction of a theoretical model developed by Leiden physicist Satish Kumar Saravanan, based on Einstein’s theory of relativity. He defends his PhD thesis on July 7th.

Do medicines arrive in the right amount at the right spot in our brain? By making a model that depicts our brain in small 'brain blocks', Esmée Vendel tries to find an answer to this question. Her new, mathematical model predicts the concentration of medicines in the brain over time and space. Vendel…

Scientists in Leiden are looking for signals in blood samples to predict whether patients will develop serious COVID-19 symptoms or not. Based on that knowledge, they will be able to propose targeted therapies to prevent serious symptoms. They hope to come up with the first results within the week.

The standard approach to build a quantum computer with Majoranas as building blocks is to convert them into qubits. However, a promising application of quantum computing—quantum chemistry—would require these qubits to be converted again into so-called fermions. Physicists from Leiden and Delft suggest…