MBB Frontier Grant

Programmable medicines

We are entering a transformational period in biomedical research, where technologies to read and write biological information have finally reached the scale and complexity of the organs we study. Gene editing, synthetic biology, synthetic vectors, single-cell biology, AI and machine learning are all converging to a new paradigm of biomedical research. These developments are nothing short of revolutionary.

Programmable drugs based on synthetic DNA and RNA will soon become the dominant class of medicines. They are poised to democratize drug development, radically narrowing the gap between basic discovery and clinical trial. Being fully synthetic, and programmable, they can be designed and engineered, instead of serendipitously discovered. We are learning to program our own cells, and this new power will radically define the future of human health and well-being.

To reach these goals, new technologies must be developed, including:

• Molecular sensors of cellular states, that can drive a desired therapeutic programme in response to complex disease states in individual cells
• Quantitative models of cell behaviour, with predictive power sufficient to guide drug design (e.g. models of DNA regulatory elements, protein structure, RNA folding, etc.)
• Therapeutic genetic circuits that predictably manipulate cell state in order to cure disease (e.g. modulation of neuronal activity, modulation of immune cell activation, induction of cell death or cell growth, adjustment of metabolic activity, etc.)
• Non-immunogenic vectors for targeted delivery of RNA or DNA to cells of interest
• Mechanisms for drug delivery across biological barriers, such as the blood brain-barrier

Synthetic biology

The field of synthetic biology encompasses the engineering of biological systems to achieve new functions and biological products that can be used in medicine and biotechnology. Areas of interest include:

• protein engineering
• design of protein and/or nucleic acid logical circuits and gates,
• genetic engineering
• novel targeting mechanisms

The potential for actual engineering of biology for the improvement of human health has never been greater. We predict that many fundamental discoveries in biology will depend on techniques and tools developed within synthetic biology and related fields. To properly understand biology, we must become even better at manipulating biology.

Metabolomic applications in precision medicine

We are only just scratching the surface of the metabolic universe and the rules that govern it. Therefore, the application of state-of-the-art mass spectrometry and NMR to different scientific questions has great potential to advance our understanding of cell function and the interaction with our environment. Metabolomics is already a fruitful tool for clinical medicine. E.g., metabolomics coupled to genomics is helping to elucidate the metabolic phenotypes in diseases and provide biomarkers for diagnosis and treatment evaluation. All common age-associated diseases, such as cardiovascular disease, cancer, diabetes type 2 and neurodegeneration, have important metabolic components that are incompletely understood. One example is the increasing focus on cancer cell metabolism and the revival of the Warburg hypothesis. Another example is provided by the recent unexpected insights into how the immune system uses endogenous and exogenous metabolites to maintain homeostasis during inflammation and infectious disease.

Cellular metabolism underpins organism homeostasis and is dysregulated in many different diseases. Accordingly, metabolomics tools are vital resources for precision medicine, e.g., biomarker analysis for predicting disease risk or treatment responses. Given the expansive universe of known and uncharacterized metabolites and the myriad ways metabolic networks interact on an organism-wide basis, many metabolic mysteries remain. Although unsupervised omics methods have revealed fascinating insights, a more detailed understanding of how the metabolic systems of humans, other animals and microorganisms adapt to environmental changes and disease conditions is needed.

Many challenges to implement metabolomics in basic science and clinical medicine remain. E.g., advanced untargeted mass spectrometry enables the simultaneous analysis of very large numbers of metabolites, but there is an urgent need to put data into a biological context by developing advanced statistical and artificial intelligence tools. Analysis of complex metabolomics datasets require the dedication of computationally- and statistics-minded researchers strongly rooted in biology. Over time, the automation of these tools will further the deployment of multi-dimensional metabolomic tools to the clinic. In addition, application of metabolic flux measurements in human cells, animal models and patients will help reveal the mechanistic underpinnings of complex metabolic diseases. Thus, while we hope that the applicant will address important basic biological questions by using a range of technologies, he/she should also have a data-driven translational vision for the technology with a view to developing new diagnostic assays.

Conditions

The successful candidate will be awarded a generous startup package, including six years employment as assistant professor and robust unconditional research funding.

Eligibility:

• PhD no more than 7 years ago
• Must fulfill the KI eligibility criteria for biträdande lektor or senior forskare

How to apply

We prefer that your application is written in English, but you can also apply in Swedish. An application must contain the following documents:

• Your CV (max 3 pages)
• Statement of research goals (max 5 pages)
• Your 3 most important papers (preprints are allowed) in PDF format
• Cover letter with contact details of 3 referees (max 1 page)

Welcome to apply at the latest on the 6 November 2022.

The application is to be submitted through the Varbi recruitment system.