Name: PyData Cambridge - 41st Meetup
Start: 2023-03-15T19:00:00Z
End: 2023-03-15T21:00:00Z
Location: Raspberry Pi Foundation

📣📣We are happy to announce the 41st PyData Cambridge meetup!📣📣
Agenda
18:45 - 🚪 Doors open (Please do not arrive earlier)
19:00 - ▶️ Introduction
19:15 - 🗣 **Dealing with medical images: Common formats, tools, and pitfalls (by Mayank Patwari)**
19:50 - 🍕 Interval - pizza and drinks provided
20:15 - 🗣 **Is Python Packages Management in GxP Environments Mission impossible? (by Jerzy Gurycz, Gur AI LTD)**
20:50 - 🍻 End (Pub - Station Tavern, Station Square)

**Title: Dealing with medical images: Common formats, tools, and pitfalls by Mayank Patwari, AstraZeneca**
Monai is a popular open-source toolkit for deep learning in medical imaging. I will demonstrate how Monai is used to improve our code and speed up medical image annotation, deep learning, and deployment of trained models. I will discuss formats used for computational storage and development of medical images, tools used to process them, and some common pitfalls which have been observed.
**\-\-\-\-**
**Title: Is Python Packages Management in GxP Environments Mission impossible? by Jerzy Gurycz**
Python and many of the open-source python packages are very popular with data science and data engineering teams in life sciences organisations. The use of open-source or in-house developed python packages in such validated environments poses strong challenges.
In my talk, I will focus on challenges with python package management in manufacturing science and technology units of pharmaceutical companies that I have dealt with recently.
Life Sciences businesses must follow GxP regulations and guidelines (good x practices, where x = M, L, C, .. as in Good Manufacturing Practices, Good Laboratory Practices, Good Clinical Practices) with long well established standards. Business users in modern companies want to move fast and be agile and competitive, and not constrained or delayed. However, avoiding GxP and CSV constraints can be FDA biologics license problems, high fines, expensive recalls of batches and most importantly endangering safety and loss of human lives. How can analytics engineering provide analytics tools to users and yet stay compliant?

## Speaker

Mayank Patwari & Jerzy Gurycz
**Mayank Patwari Bio:**
Mayank Patwari is a Senior Deep Learning Engineer at AstraZeneca, where he is involved in a number of exciting medical imaging projects.

Mayank has twin competencies in Machine Learning and Medical Engineering, making him uniquely qualified to contribute to the development of cutting-edge medical imaging technologies.

Mayank holds a Doctor of Engineering from FAU Erlangen-Nurenberg, where he conducted doctoral research at the Precision Learning Group at the Pattern Recognition Lab of the Department of Computer Science.

**Jery Gurycz Bio:**
Jerzy is a statistician, software architect, engineer, and data scientist (yes, it is possible !) with over 20 years of experience in programming and consulting. He has effectively used statistical tools (SAS, IBM SPSS, Statistica) and BI systems and architected and deployed solutions. Software engineering experience coding in Java, Python, C, C++, R, SQL, Scala, and Hadoop clusters with Spark - all to deliver predictive analytics.

Jerzy assists customers in analytics solutions delivery and works as an analytics engineer using AWS, and GCP architectures as an independent consultant/contractor. He has worked for 3 of the top 10 largest pharma companies (and 4 most profitable in 2022 from the Fortune 500 list) and holds a PhD in mathematics and a Higher Certificate in Statistics with Distinction from The Royal Statistical Society.

**Code of Conduct**
PyData is dedicated to providing a harassment-free event experience for everyone, regardless of gender, sexual orientation, gender identity, and expression, disability, physical appearance, body size, race, or religion. We do not tolerate harassment of participants in any form.
The PyData Code of Conduct governs this meetup. ( http://pydata.org/code-of-conduct.html ) To discuss any issues or concerns relating to the code of conduct or the behaviour of anyone at a PyData meetup, please contact NumFOCUS Executive Director Leah Silen (leah@numfocus.org) or organizers.

Federico

Anna Maria Tsakiroglou

Ole Schulz-Trieglaff

Tom Burdge

Leandro Nunes

PyData Cambridge

PyData

Raspberry Pi Foundation

Technology

Python

Statistical Computing

Big Data

High Scalability Computing

Machine Learning

Data Analytics

Data Visualization

Neural Networks

Data Mining

Data Science

Open Source Python

Deep Learning

Data Science using Python

PyData Cambridge - 41st Meetup

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