Although the biosimilar space is still growing and evolving in the U.S., it is comparatively well-established in India. According to the Generics and Biosimilars Initiative (GaBI), the first “similar biologic” was approved and marketed in India in 2000 — some 15 years before the U.S. approved its first biosimilar. India also has a much more mature biosimilar manufacturing ecosystem and regulatory environment than most other parts of the world. As such, the country can provide valuable lessons about what it takes to establish a thriving biosimilar market in terms of accessibility, competition, regulatory strategy, and other facets.
In the first of this two-part article, Sandoz's Cindy Cao shares lessons learned from working with the FDA and reveals that there is still a lot of room for exploration and innovation in biosimilar development.
I recently attended the Association for Accessible Medicines (AAM) Biosimilars Council’s Leading on Biosimilars conference.In addition to the many tidbits of knowledge I took away from this event, two terms kept resurfacing throughout the conference I feel are worth delving into more deeply.
Newly-appointed Pfenex CEO, Eef Schimmelpennink, faces the challenge of determining how to adapt Pfenex to a constantly changing future. Though it's still very early in his tenure, Schimmelpennink highlights some areas he will keep in mind as he steers Pfenex's future biosimilars onto the market.
In a presentation at the 2017 World Biosimilars Congress, Asif Mahmood, disease area safety and strategy lead at Pfizer, shed some light on global risk management strategies and the challenges of launching these programs.
In a recent article, I discussed the market opportunities and reimbursement system in Russia. But in addition to this snapshot of the market, my conversation with BIOCAD's Roman Ivanov highlighted how the Russian biosimilar regulatory system was established, as well as the challenges BIOCAD has faced during it evolution.
Although the biosimilar space is still growing and evolving in the U.S., it is comparatively well-established in India. According to the Generics and Biosimilars Initiative (GaBI), the first “similar biologic” was approved and marketed in India in 2000 — some 15 years before the U.S. approved its first biosimilar. India also has a much more mature biosimilar manufacturing ecosystem and regulatory environment than most other parts of the world. As such, the country can provide valuable lessons about what it takes to establish a thriving biosimilar market in terms of accessibility, competition, regulatory strategy, and other facets.
Innovation has long been a topic of focus in the pharmaceutical industry, with developers striving for it, regulators and payers demanding it, and everyone — from patients to manufacturers — worrying about who is going to pay for it. Something that often gets lost in the conversation is: What exactly do we mean when we talk about “innovation”?
If you are charged with any of the tasks that lead to a successful product launch in the pharmaceutical industry, you know how critical it is to execute a multitude of steps successfully. Among these are agreement by marketing on the look and design of the campaign, completion of clinical trials, project management, testing of active pharmaceutical ingredients, the completion of a trial production batch, receipt of all materials at the production site, production scheduling, regulatory agency submissions, trademark registration, and a host of others.
Investing in training for employees in the life sciences and biopharmaceuticals industries generates quantifiable returns that go far beyond simply imparting specific, task-oriented knowledge. For example, effective and thoughtfully planned onboarding and sustainable training are key elements in attaining a culture of quality throughout the organization. Furthermore, inadequate training contributes to process and product variability.
Microbial control for non-sterile manufacturing helps to ensure the safety and efficacy of pharmaceuticals. Products that are compromised with excessive amounts of microorganisms, specified microorganisms, or objectionable microorganisms may not be effective or could be dangerous to consumers. Unfortunately, the regulations governing non-sterile manufacturing are not as clear or as abundant as those for sterile manufacturing. This leads many manufacturers to utilize risk assessment analysis tools to adapt portions of sterile manufacturing guidelines when developing environmental monitoring programs for non-sterile environments.
The modern biopharmaceutical/biotechnology manufacturing facility contains many sophisticated control, data logging, and data archiving systems. Massive amounts of data are collected from sources such as raw materials analysis, process outputs, and final quality assessments, which are stored in data warehouses.
By William Whitford, Strategic Solutions Leader, BioProcess, GE Healthcare Life Sciences
The industry is abuzz with talk about continuous biomanufacturing (CB), and its virtues have been well described. Here we will look at some of the barriers or concerns perceived to limit its value to the industry. Justified or not, quite a few concerns have been expressed regarding the implementation of this new, rather disruptive technology.
A global specialty biopharmaceutical company entered into a public-private contract worth $220 million with the Biomedical Advance Research and Development Authority (BARDA) in 2012. Its primary goal was to establish a Center for Innovation in Advanced Development and Manufacturing (CIADM) to address challenges encountered in developing biodefense medical countermeasures.
We need to create spaces that help produce the spark of genius, encourage new ways of thinking and foster collaboration across disciplines.
Whether these proteins are produced by recombinant DNA technology or extracted from sources such as plasma, they need to be highly purified — and the purification process must satisfy a variety of regulations.
In a scenario where manufacturing processes move to a continuous flow, analyzers are producing data simultaneously, necessitating real-time processing and making the existence of cloud-based tools for data management crucial.
Both multivariate analysis (MVA) and design of experiments (DoE) methods have numerous applications for simplifying the learning from large data sets and experimentation.
