Post event: Anything new for oncology?

Post event: Anything new for oncology?

Post event: Anything new for oncology?

Lately, Basel Biometric Section and EFSPI organized a webinar “Estimands addendum is final: Anything new for oncology?”. You can find the program, the slides, a recording of the entire event, and a document that answers questions that were raised in the chat during the event on the BBS webpage.

In addition to Hannes Buchner from Staburo GmbH (1:23:53 of recording) and Ingolf Griebsch from Boehringer Ingelheim (1:12:30), Kaspar Rufibach from Roche (0:20), who is a member of the BBS board, Anja Schiel from the Norwegian Medicines Agency (6:55), Renaud Capdeville from Novartis (40:40), Tina Nielsen from Roche (54:33) and Stefan Englert from AbbVie (1:46:58) gave exciting lectures, which can be viewed on the webpage.

The panel discussion in the end was held from all speakers plus Rob Hemmings from Consilium and Michael Wenger from Novartis.

With just short of 400 registered participants the event was a huge success!

Data analysis, clinical biostatistics and more.

Senior Biostatistician (m/w/d) in Munich

Senior Biostatistician (m/w/d) in Munich

Die Staburo GmbH ist ein Münchner Biostatistikunternehmen, das auf statistische Beratung und Programmierung im Umfeld von klinischen Studien spezialisiert ist. Aufbauend auf unseren 6 Säulen (Klinische Statistik, Translationale Medizin & Biomarker, Pharmakokinetik/-dynamik, Nutzenbewertung, Nichtklinische Statistik und Statistische Programmierung mit CDISC) erarbeiten wir in Projektteams maßgeschneiderte Lösungen.
Unsere Kunden sind renommierte Pharmafirmen (7 der Top 20), CROs und Biotechunternehmen, mit denen wir flexibel und gerne auch vor Ort zusammenarbeiten.

Zur Erweiterung unseres Teams suchen wir zum nächstmöglichen Zeitpunkt zur Festanstellung einen

Senior Biostatistician (m/w/d)

 
Ihre Aufgabengebiete:
  • Auswertung klinischer Studien der Phasen I – IV und Präsentation der Ergebnisse
  • Statistische Programmierung (SAS mit SDTM und ADaM; R)
  • Programmvalidierung von klinischen Studien
  • Unterstützung bei der Studien- und Patientenfallzahlplanung
  • Erstellung der SAPs und der Studiendesigns
  • Ansprechpartner für unsere Mitarbeiter und Kunden
Ihr Profil:
  • Erfolgreich abgeschlossenes Studium im Bereich Statistik, Mathematik, oder eine vergleichbare Ausbildung
  • Sehr gutes methodisches Wissen im Bereich klinische Statistik
  • Mehr als 2 Jahre Berufserfahrung als Statistiker mit Verantwortung für klinische Studien
  • Sehr gute EDV Kenntnisse, besonders mit statistischen Analysetools (SAS, R)
  • Schnelle Auffassungsgabe und analytisches Denkvermögen
  • Teamfähigkeit und ein hohes Maß an Eigeninitiative
Was wir Ihnen bieten:

Es erwartet Sie eine abwechslungsreiche, eigenverantwortliche Tätigkeit mit sehr guten Entwicklungsmöglichkeiten. Wir legen großen Wert auf Kommunikation, flache Hierarchien, offene Unternehmenskultur und ein harmonisches Arbeitsumfeld. Unser Standort in München bietet sehr gute Arbeitsbedingungen, moderne Büroräume und eine schnelle Anbindung an den öffentlichen Nahverkehr.

Neugierig geworden?

Dann informieren Sie sich auf unserer Internetseite: www.staburo.de und werden Teil unseres stetig wachsenden Teams!
Wir freuen uns über Ihre vollständigen Bewerbungsunterlagen mit Angabe Ihrer Gehaltsvorstellung. Für eine schnelle Abwicklung des Bewerbungsprozesses bitten wir um eine E-Mail-Bewerbung an: bewerbung@staburo.de.

Hier finden Sie diese Stellenanzeige als PDF Datei.

 

Staburo @ Joint EFSPI / BBS Webinar: Estimands addendum is final: Anything new for oncology?

Staburo @ Joint EFSPI / BBS Webinar: Estimands addendum is final: Anything new for oncology?

Staburo @ Joint EFSPI / BBS Webinar: Estimands addendum is final: Anything new for oncology?

We are very proud that Staburo’s Managing Director Dr. Hannes Buchner will be a speaker and will talk about “Treatment switching: challenges, estimands, and estimators”.

All information on registration and agenda of the event can be found on the BBS website.

This event was planned as a full-day seminar on the Novartis campus, but due to the current situation, the event will be performed in a webinar format.

Background: After the publication of the final version of the ICH E9 addendum, the BBS jointly with EFSPI would
like to offer a full-day seminar on the broad topic of estimands in oncology drug development. The
event will feature talks from statisticians and clinicians in industry, regulatory agencies, and academia.
It is the explicit intention of the event to extend the estimand discussion to those who partner with
statisticians in drug development, i.e. clinicians, regulatory colleagues, etc. For this reason, many of
the talks in the program are shared between a statistician and a clinician.
The intention is to make this the first of a series of events dedicated to estimands for specific
therapeutic areas. We start with oncology and envisage further seminars on, e.g., neuroscience.

The organizing committee members are Evgeny Degtyarev, Kaspar Rufibach, Bibiana Blatna, MarieLaure Casadebaig, Lynda Grinsted, Lorenzo Guizzaro, Wolfgang Kothny, Giusi Moffa, Hans-Jochen Weber. The event is supported by the European special interest group “Estimands in oncology”, sponsored by PSI and EFSPI, which is also an ASA scientific working group:
http://www.oncoestimand.org.

Initially, this event was planned as a full-day seminar on the Novartis campus. Given the current COVID19 situation we turn this event into a series of webinars. If you’d like to attend please fill out the registration form. After registration you will receive a calendar invite with a webex link. Slides and recordings of some of the talks will be made available after the event on the BBS webpage, both pending speaker approval.
The webinar is free of charge.

Data analysis, clinical biostatistics and more.

System Administrator (f/m/d)

System Administrator (f/m/d)

Staburo GmbH is a data science company, specialized in statistical consulting, programming and bioinformatics for healthcare projects. Our core competencies include Clinical Statistics, Translational Medicine & Biomarkers, Phase I & Pharmacokinetics/-Dynamics, Data Transparency, Health Technology Assessment and Bioinformatics. Our customers are international pharmaceutical companies (7 of the top 20), CROs, biotech companies and medical device manufacturers. Our steadily growing team of 35 experts supports our clients efficiently from study design to data analysis and finally the disclosing and posting of trial results.

To expand our team in Munich, we are looking for a

System Administrator (f/m/d)

 
Your responsibilities will include:
  • Administration and development of IT infrastructure
  • Administration of Windows servers (active directory hybrid deployment) and Linux servers
  • Planning and rollout of deployment of software to clients
  • Administration of network infrastructure including firewall and VPN
  • Administration of project-based access rights
  • Validation of software systems and management of backup solution
  • General IT support for the team
Your profile:
  • Apprenticeship as system integrator, university degree in computer science, or equivalent education
  • At least two years of experience as system administrator
  • At least two years of experience with Windows Server (admin-level)
  • Knowledge of terminal server solution with RDP
  • Very good IT expertise, with knowledge in software and platform validation according to GAMP5
  • Good English skills, German is an advantage
What we offer you:

As a quality provider of statistical consulting we truly believe that delivery of high-quality services is the foundation of our stable and growing team. Therefore, we give you time for your core job competencies by minimizing organizational burden. Our continued trainings keep you up-to-date on all regulatory requirements. We value communication, flat hierarchies, open corporate culture and a harmonious work environment. We offer comprehensive individual development opportunities and flexible working hours.

Curious?

Check our website: www.staburo.de and become part of our constantly growing team! We look forward to receiving your application. Please send this by e-mail to: bewerbung@staburo.de. We look forward to meeting you soon!

Here you find our jod advertisement in PDF format.

 

How to Avoid Overfitting, Precision Medicine in Action & Tumour Growth Modelling – three PSI contributions

How to Avoid Overfitting, Precision Medicine in Action & Tumour Growth Modelling – three PSI contributions

 

Staburo’s 2020 PSI contributions in webinar format on 26 May (15:00 – 17:15 CET)

Since the 2020 PSI conference will unfortunately not take place, we decided to share our PSI contributions in an online live webinar with our colleagues. Staburo biostatisticians Nicole Krämer, Laura Schlieker and Hannes Buchner will talk about “How to Avoid Overfitting, Precision Medicine in Action & Tumour Growth Modelling” on 26 May (15:00 – 17:15 CET). You find the agenda and abstracts of the talks  below.

If you want to join the webinar please send us an email with your name to info@staburo.de or use the sign up button below. We will not use any of your personal information for other purposes than for giving you access to the online live presentations. Participation is free of charge. We are looking forward to this online event with you! 

Sign up now!

 

Abstract Nicole Krämer’s talk (approx. 15:00 – 15:45 CET on 26 May):

This presentation in based on joint work by Nicole Krämer, Carina Ittrich (Boehringer Ingelheim) and Josef Höfler (Staburo).

The identification of patient subgroups who derive benefit from a new treatment is of crucial importance in precision medicine. For a clinical trial that compares an experimental treatment E to a control treatment C using a time-to-event endpoint, this may translate to finding a subgroup in which the hazard ratio E versus C is particularly low.

Many subgroup identification algorithms have been proposed and studied. They range from cut-off optimization for single biomarkers to the virtual twin method or high-dimensional gene-expression signatures. In general, they differ in the underlying estimand and in the way the subgroup is identified. However, due to their data-driven nature, the estimated relative treatment benefit (e.g. the hazard ratio) within the identified subgroup is almost always biased. This in turn has considerable implications on the clinical development as these ‘naïve’ subgroup effects are too optimistic and cannot be reproduced in a new trial.

We propose cross-validation to obtain a more realistic subgroup effect. In each cross-validation split, the subgroup identification algorithm is applied to the training set. The obtained rule is used to assign patients in the test set to the subgroup or its complement. We define the cross-validated relative treatment benefit as the relative treatment benefit based on this subgroup assignment.

In extensive simulations, we show that on average, the cross-validated relative treatment benefit is very close to the true relative treatment benefit. The approach is further illustrated in an application to a breast cancer study.

 

Abstract  Laura Schlieker’s talk (approx. 15:45 – 16:30 CET on 26 May):

This presentation in based on joint work by Laura Schlieker, Nicole Krämer, Volker Heinemann (LMU Munich), Arndt Stahler (LMU Munich) and Sebastian Stintzing (LMU Munich).

The choice of the right treatment for patients based on their individual genetic profile is of utmost importance in precision medicine. To identify potential signals within the large number of biomarkers it is mandatory to define criteria for signal detection beforehand and apply appropriate statistical models in the setting of high dimensional data.

For the identification of predictive and prognostic genetic variants as well as tumor mutational burden (TMB) in patients with metastatic colorectal cancer, we derived the following pre-defined and hierarchical criteria for signal detection.

  1. All biomarkers identified via a multivariate variable selection procedure
  2. If a) reveals no signal, all biomarkers with adjusted p-value ≤ 0.157
  3. If neither a) nor b) reveals signals, the top 5 biomarkers according to sorted, adjusted p-value

Regularized regression models were used for variable selection, and the stability of the selection process was quantified and visualized. Selected biomarkers were analyzed in terms of their predictive potential on a continuous scale.

With our analyses we confirmed the predictive potential of several already known biomarkers and identified additional promising candidate variants. Furthermore, we identified TMB as a potential prognostic biomarker with a trend towards prolonged survival for patients with high TMB.

Our analyses were supported by power simulations for the variable selection method, assuming different prevalences of biomarkers, numbers of truly predictive biomarkers and effect sizes.

 

Abstract Hannes Buchner’s talk (approx. 16:30 – 17:15 CET on 26 May):

This presentation in based on joint work by Hannes Buchner and Gabriele Bleckert (Staburo).

In oncology, reliable estimates of progression-free-survival (PFS) are of highest importance because of high failure rates of phase III trials (around 60%). However, PFS-estimations on early readouts with less than 50% of events observed do not use all available information from tumour measurements over time.

We project the PFS-event of each censored patient by using a mixed model describing the tumour burden over time. RECIST-criteria are applied on estimated patient-specific non-linear tumour-trajectories to calculate the projected time-to-progression. PFS is compared between test and reference by hazard ratios.

Several phase III and II simulations with 1000 runs each with 2000 or 80 patients, 6 months accrual and 2 (scenario-1) or 6 months (scenario-2) follow-up were performed. All simulations are based on a published optimal parameterisation of tumour-growth in NSCLC which implies a time-dependent HR.

 

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Data analysis, clinical biostatistics and more.