Invitris radically simplifies how we create novel biological drugs. Our patent-pending technology platform turns DNA into synthetic proteins and was recently featured in the Science magazine. It makes bioengineering >10,000x more efficient at <100x lower costs of material.Our killer application is enabling the newest generation of synthetic bacteriophages to combat antibiotic-resistant infections, which are threatening to cause more deaths than all cancers combined. As CEO & co-founder of Invitris, I hold all business-related responsibilities including:- Acquisition of capital,- Team & stakeholder management,- Licensing strategies,- Sales planning, and- Market & competitor research.Our vision is to enable all clinics around the world to generate their own personalized biological on demand, anytime and anywhere.

Following my passion for bio sciences and data science, I am offering a range of computational services to both academic and private laboratories. These services include pure bioinformatics, data analytics, machine learning, and also research transfer into viable business models.Any requests please via https://www.patrick-grossmann.com.

We are currently witnessing a paradigm change in how we do biology: single-cell analysis. Analyzing biological mechanisms of diseases such as cancer at the a single-cell level provides us new understanding how diverse cells act and how we need to take this into account when utilizing this knowledge to provide better treatment to patients.At DEOXY, we are doing exactly this. We are developing novel technology to efficiently analyze the expression of hundreds of genes in 10,000s of cells in parallel and in single-molecule sensitivity level to uncover new biological disease mechanisms.My role with DEOXY is:- Establish DEOXY's Business Development.- Create focus group studies with scientists and clinicians to identify open customer needs.- Conduct market research to assess commercialization potential.- Develop strategies to position DEOXY's value propositions within the competitive landscape.- Business case modeling and sales planning.

Our goal is to innovate the current process industry by leveraging digital technologies.Joining forces of engineering and plant operations, my primary role is to develop, implement, and market novel data-driven business models that guarantee value for our customers.

As integral part of the MBA curriculum, my project assignment includes:• Leading an agile project team with independent work streams,• Developing commercial strategies around Predictive Maintenance, • Assessing the competitive technological landscape through market research analysis, and• Brainstorming creative approaches to achieve digital transformation on large scale.

Appointment at Harvard Medical School as a full time visiting graduate student conducting doctoral research studies to promote precision medicine and translational sciences.http://hms.harvard.edu/faculty-search?LastName=Grossmann&FirstName=Patrick&id=BXoUUHsI

• Computational Imaging and Bioinformatics Laboratory • Medical Physics Division • Dept. of Radiation Oncology • Harvard Medical School My doctoral research studies in Dr. Hugo Aerts' lab deal with the application of integrative statistical methods on medical imaging and molecular data in order to benefit from complementary data sources delivered by independent experiments and, as a result, to gain novel insights. The overall goal is digital phenotyping of tumors for precision medicine. The data analysis I perform advance(A) Radiomics and Radiogenomics, an emerging field that seeks to translate medical images (e.g. from CT or MRI modalities) into minable data and to afterwards extract quantitative features describing important tumor characteristics such as shape, edge, and texture of a tumor. My goal is to connect these imaging features to biological data such as gene expression and mutation data,(B) Toxicogenomics, which seeks to understand how molecular mechanisms in cells exposed to potentially toxic chemicals or drugs are altered, and(C) Pharmacogenomics, which aim at assessing how drug responses are related to the genomic profile of an individual patient.Throughout my analyses, I lay a focus on reproducibility. It is my strong belief that this is the only way to establish new knowledge as data becomes more and more complex.http://www.cibl-harvard.org/patrickgrossmann

• Computational Biology Group • Dept. of Biosystems Science and EngineeringMy externally conducted Master's Thesis in the group of Prof. Dr. Niko Beerenwinkel contains research on the novel idea of the impact of a specific set of driver genes and the mutator phenotype in a stochastic model of tumorigenesis. I was co-supervised by Prof. Dr. Ellen Baake in Germany.

• Faculty of Technology• Faculty of Biology• Center of BiotechnologyIn Bielefeld I was enrolled in the Master of Science program "Bioinformatics & Genome Research" (Faculty of Technology), where I focused on computational biology, statistical data analysis, and more general programming skills. Here I found out that my interest switched from discrete algorithmics to applied statistics and stochastics. I am convinced that the interpretation of biological phenomenons can best be accomplished by use of techniques that take into account the fact that biology does not behave in discrete but in stochastic events.

• Functional Genomics Laboratory • Dept. of Biostatistics and Computational Biology • Harvard School of Public HealthDuring this internship at the Computational Biology and Functional Genomics Laboratory headed by Prof. Dr. John Quackenbush, I presented a statistical analysis of all >600 published human breast cancer gene signatures with respect to their ability to predict overall survival among molecular subtypes of breast cancer. Here, I worked closely together with my supervisor Dr. Aedin Culhane.

Development and installation of bioinformatic tools/pipelines for metagenomic and single cell analysis. Evaluation of metagenomic and single cell assemblies. Here, I worked together with Dr. Alexander Sczyrba and Andreas Bremges.

Documentation of passive infrastructure and establishment of supporting guidelines.

External Bachelor's Thesis research in the group of Computational Systems Biology headed by Prof. Dr. Jörg Stelling on the sequence analysis of transmembrane proteins in yeast with respect to a potential correlation of signal peptide and first trans-membrane domain. I was supervised by Dr. Hans-Michael Kaltenbach and Dr. Fabian Rudolf as well as Prof. Dr. Jens Stoye in Germany.