Kliniske forsøg

Methodologies for Biosimilar Product Development covers the practical and challenging issues that are commonly encountered during the development, review, and approval of a proposed biosimilar product. These practical and challenging issues include, but are not limited to the mix-up use of interval hypotheses testing (i.e., the use of TOST) and confidence interval approach, a risk/benefit assessment for non-inferiority/similarity margin, PK/PD bridging studies with multiple references, the detection of possible reference product change over time, design and analysis of biosimilar switching studies, the assessment of sensitivity index for assessment of extrapolation across indications without collecting data from those indications not under study, and the feasibility and validation of non-medical switch post-approval.Key Features:Reviews withdrawn draft guidance on analytical similarity assessment.Evaluates various methods for analytical similarity evaluation based on FDA's current guidelines.Provides a general approach for the use of n-of-1 trial design for assessment of interchangeability.Discusses the feasibility and validity of the non-medical switch studies.Provides innovative thinking for detection of possible reference product change over time.This book embraces innovative thinking of design and analysis for biosimilar studies, which are required for review and approval of biosimilar regulatory submissions.

King Charles has entertained a long-standing love affair with alternative medicine. This book describes his passion as it developed during the last 40 years. The King's beliefs, opinions, and ambitions are critically assessed against the background of the scientific evidence. In most instances, the contrast could not be starker.

This book is an attempt to unveil the hidden potential of the enormous amount of health information and technology. This book is written with the intent to uncover the stakes and possibilities involved in realizing personalized health-care services through efficient and effective deep learning algorithms.

A disease is defined as rare if the prevalence is fewer than 200,000 in the United States. It is estimated that there are more than 7,000 rare diseases, which collectively affect 30 million Americans. This diverse and complex disease area poses challenges for patients, caregivers, regulators, drug developers and other stakeholders.

Preceded by: Laboratory animal anaesthesia / Paul Flecknell. Fourth edition. 2016.

Intended to be a single source of information, this book covers a wide range of topics on the changing landscape of drug R&D, emerging applications of big data, AI and machine learning in drug development, and the build of robust data science organizations to drive biopharmaceutical digital transformations.