Synthetic Biology

University of Pavia
Dep. of Electrical, Computer and Biomedical Engineering
Laboratory of Bioinformatics,
Mathematical Modelling and Synthetic
Biology
Web site: http://lab-bioinfo.unipv.it
Lab Director: Prof. Paolo Magni
Contact: [email protected]
Dipartimento di Ingegneria
Industriale e dell’Informazione
labmedinfo.org
lab-bioinfo.unipv.it
• Bioinformatics
• Mathematical
Modelling of biological
systems
• Synthetic Biology
• Clinical Data Mining
• Biomedical Knowledge
Management
• Decision Support Systems
• Telemedicine
• E-learning
BMI director: Prof. Riccardo Bellazzi
BMS director: Prof. Paolo Magni
Bioinformatics
Mathematial
Modelling
Synthetic Biology
Areas
Bioinformatics
Mathematical modelling
Synthetic Biology
Areas
Bioinformatics
Mathematical modelling
Synthetic Biology
Bioinformatics (1/4)
• Next Generation Sequencing (NGS)
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Implementation and validation of data analysis pipelines
for several sequencing applications;
optimization of cluster and cloud environments;
development of new algorithms and procedures for NGS
data analysis.
Ongoing collaborations
•Need to be
Velocity
analyzed quickly.
Volumes
Big Data problem
Variety
•Large amount of
data.
•Different types of
structured and
unstructured
data.
new spin-off of the University of Pavia, born to
provide bioinformatic solutions in NGS data anaysis
Susanna Zucca
1 marzo 2016
Bioinformatics (2/4)
Applications:
Workflow:
Diagnosis of
neurological
diseases
Stroke
diagnosys
Susanna Zucca
1 marzo 2016
Bioinformatics (3/4)
• Network-based pharmacology
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Network-based approaches to integrate
different data and knowledge sources;
identification of combinations of hit targets to
act with pharmacological therapy.
Susanna Zucca
1 marzo 2016
Bioinformatics (4/4)
• Tissue Engineering and Developmental Biology
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Implementation of tools for the monitoring of stem cell pluripotency;
extraction of quantitative measures of the cell status from wholegenome expression profiles.
Susanna Zucca
1 marzo 2016
Areas
Bioinformatics
Mathematical modelling
Synthetic Biology
Susanna Zucca
1 marzo 2016
Mathematical Modelling (1/4)
• Model-based drug development
Experimental Setting
Data Collection
CLINICAL
0
PRECLINICAL
Susanna Zucca
1 marzo 2016
Modelling - Data Analysis
Mathematical Modelling (2/4)
• Pharmacokinetic/pharmacodynamic (PK/PD)
models
What body does to the
drug
Susanna Zucca
What drug
does to the body
1 marzo 2016
Mathematical Modelling (3/4)
Advanced expertise in
• Bayesian techniques (and Markov Chain Monte Carlo algorithms)
• Population analysis
• Deconvolution methods
PK/PD models
• Support of drug development and registration (in vitro, preclinical,
clinical studies)
• Development of PK-PD models to quantitatively describe kinetics,
mechanism of action and the effects on relevant endpoints of new
compounds currently under investigation
Research Areas
• Oncology: solid tumor, blood cancer, biomarkers, drug-drug interaction
• Biologicals: autoimmune diseases
• Study design: paediatrics, optimal design
Tools
• Matlab, R, NONMEM, Monolix, WinBUGS, Stan,
SimulX, PsN, Berkeley-Madonna
Susanna Zucca
1 marzo 2016
Sharing knowledge to improve drug development
Susanna Zucca
1 marzo 2016
Mathematical Modelling (4/4)
• Collaborations
Susanna Zucca
1 marzo 2016
Future perspectives
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Move to the system pharmacology: integrating
more information about pathways and
mechanisms in the mathematical models
Participate in a foundation for the continuation of
the DDMoRe project and the maintenance of its
products
New EU projects (including IMI)
New collaborations
New peoples
Susanna Zucca
1 marzo 2016
Areas
Bioinformatics
Mathematical modelling
Synthetic Biology
Susanna Zucca
1 marzo 2016
Synthetic Biology (1/5)
De-novo synthesis of novel
organisms
Design of supplementary
functions in existing organisms
Bottom-up design in biological engineering:
Mathematical models
Input
Datasheets
Susanna Zucca
Predictable biological functions
Output
System 1
1 marzo 2016
System 2
Synthetic Biology (2/5)
• Medicine (e.g. novel methods for
drug production)
• Energy
(e.g.
optimized
production of biofuels from
waste or renewable materials)
• Environment (e.g. detection of
toxic compounds)
• Information processing
Susanna Zucca
1 marzo 2016
Synthetic Biology (3/5)
• Typical workflow for the realization of novel artificial biological functions:
Susanna Zucca
1 marzo 2016
Synthetic Biology (4/5)
• Basic research studies to facilitate the design
of predictable functions:
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Investigate predictable design via model systems
with diverse synthetic circuit architectures
Design of user-friendly genetic tools and predictive
mathematical models
• Applied research studies:
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Production of biofuels from industrial waste
Low-cost synthesis of biopolymers
Automatic control schemes for recombinant protein
production
Susanna Zucca
1 marzo 2016
Synthetic Biology (5/5)
• New research fields…
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Metabolic engineering
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CRISPR-dCAS9 gene regulation
Susanna Zucca
1 marzo 2016
University of Pavia
Dep. of Electrical, Computer and Biomedical Engineering
Grazie per l’attenzione!