Space product devices for control and regulation of technological processes
From A to Z, The Wiley Encyclopedia of Packaging Technology, Third Edition covers all aspects of packaging technologies essential to the food and pharmaceutical industries, among others. This edition has been thoroughly updated and expanded to include important innovations and changes in materials, processes, and technologies that have occurred over the past decade. It is an invaluable resource for packaging technologists, scientists and engineers, students and educators, packaging material suppliers, packaging converters, packaging machinery manufacturers, processors, retailers, and regulatory agencies. In addition to updating and improving articles from the previous edition, new articles are also added to cover the recent advances and developments in packaging. Content new to this edition includes:. Advanced packaging materials such as antimicrobial materials, biobased materials, nanocomposite materials, ceramic-coated films, and perforated films.VIDEO ON THE TOPIC: 21 CFR Part 820 - Quality System Regulation - 21 CFR 820.30 Medical Device Design Control Guidelines
Dear readers! Our articles talk about typical ways to resolve Space product devices for control and regulation of technological processes, but each case is unique.
If you want to know, how to solve your particular problem - contact the online consultant form on the right or call the numbers on the website. It is fast and free!
- Technological convergence
- U.S. Food and Drug Administration
- New Tech, New Threats, and New Governance Challenges: An Opportunity to Craft Smarter Responses?
- Top 10 Technology Trends for 2020
- Internet of things
- Privacy and Information Technology
- How Smart, Connected Products Are Transforming Competition
- Technology and the Future of Healthcare
They should be considered all together. The points to consider are not intended to be new guidance. They are intended to provide clarity to both industry and regulators and to facilitate the preparation, assessment, and inspection related to applications filed for marketing authorizations. The development approach should be adapted based on the complexity and specificity of product and process; therefore, applicants are encouraged to contact regulatory authorities regarding questions related to specific information to be included in their application.
Using the Quality by Design QbD approach does not change regional regulatory requirements but can provide opportunities for more flexible approaches to meet them. In all cases, good manufacturing practice GMP compliance is expected. Scientific rationale and quality risk management QRM processes are used to reach a conclusion on what are critical quality attributes CQAs and critical process parameters CPPs for a given product and process.
In some risk management tools, the ability to detect the harm detectability also factors in the estimation of risk. It is based on the probability of occurrence and detectability and therefore can change as a result of risk management. Considerations for identifying and documenting CQAs can include the:. Considerations for identifying and documenting CPPs can include the:. A well-developed control strategy will reduce risk but does not change the criticality of attributes.
Lifecycle of the Control Strategy. It can be refined for use in commercial manufacture as new knowledge is gained. Changes could include acceptance criteria, analytical methodology, or the points of control e. Suitability of Control Strategy at Different Scales. The design and need for scale-up studies can depend on the development approach used and knowledge available. QRM tools can be used to guide these activities.
This assessment might include risks from processing equipment, facility environmental controls, personnel capability, experiences with technologies, and historical experience prior knowledge.
The purpose of specifications and CoAs remains the same in the case of RTRT, but the way to develop them is different. Process for a Batch Release Decision. Different development approaches lead to different control strategies.
Regardless of the control strategy, the batch release process should be followed. For a batch release decision, several elements should be considered. See in the figure below an illustration of the elements of the batch release process leading to the batch release decision. There are regional differences in the regulation of batch release across the ICH regions e.
The PQS elements also facilitate regulatory compliance e. System-related data for the current batch manufactured e. In the enhanced approach, there is an increased focus on process monitoring, which can provide the opportunity to perform continuous process verification. Any deviation or atypical event that occurs during manufacturing e. Product-related data based on the manufacturing process.
Elements of the control strategy are defined and proposed in the marketing authorization dossier and agreed to by the regulators. Manufacturers should define, manage, and monitor product-related data from batches manufactured according to the control strategy. These will be regularly assessed and reviewed during audits and inspections. The batch release process leading to the batch release decision can be performed by more than one quality individual depending on the regional regulatory requirements and company policy:.
This document is intended to provide suggestions on the type of information and the level of documentation that is appropriate to support a proposal for enhanced QbD approach. The type of information, as suggested in this document, is considered supportive and is intended to facilitate assessment and inspection without increasing the regulatory requirement.
Companies might consider, especially for QbD-containing submissions, an internal peer review process to assure quality, clarity, and adequacy of the regulatory submission. For submissions containing QbD elements e. However, sufficient supporting information and data should be submitted in the application to address the following:.
The following sections include examples of background information that can be considered by both companies and regulatory authorities to assure scientific risk-based regulatory decisions. Risk Management Methodologies. The applicant should consider providing information of sufficient detail to demonstrate how the conclusions were reached, which can include:. Design of Experiments. The factors to be studied in a DoE could come from the risk assessment exercise or prior knowledge.
Inclusion of a full statistical evaluation of the DoEs performed at early development stages e. A summary table of the factors and ranges studied and the conclusions reached will be helpful.
Submitters should indicate if the factors are expected to be scale-dependent. Manufacturing Process Description. Where relevant, applicants can also consider submitting postapproval change management plans or protocols to manage postapproval manufacturing changes based on regional requirements. A model is a simplified representation of a system using mathematical terms. Models can enhance scientific understanding and possibly predict the behavior of a system under a set of conditions.
Mathematical models can be used at every stage of development and manufacturing. They can be derived from first principles reflecting physical laws such as mass balance, energy balance, and heat transfer relations , or from data, or from a combination of the two.
There are many types of models and the selected one will depend on the existing knowledge about the system, the data available, and the objective of the study. This document is intended to highlight some points to consider when developing and implementing mathematical models during pharmaceutical product development, manufacturing and throughout the product lifecycle.
Other approaches not described in this document can also be used. Categorization of Models. Models can be categorized in multiple ways. The categorization approaches used throughout this document are intended to facilitate the use of models across the lifecycle, including development, manufacturing, control, and regulatory processes.
The level of oversight should be commensurate with the level of risk associated with the use of the specific model. The following is an example of such a categorization:. Medium-Impact Models: Such models can be useful in assuring quality of the product but are not the sole indicators of product quality e.
High-Impact Models: A model can be considered high impact if prediction from the model is a significant indicator of quality of the product e. For the purpose of implementation, models can also be categorized on the basis of the intended outcome of the model. Within each of these categories, models can be further classified as low, medium or high, on the basis of their impact in assuring product quality.
Models within this category can have different levels of impact. For example, a model for design space determination would generally be considered a medium-impact model, while a model for formulation optimization would be considered a low-impact model.
Models for supporting analytical procedures can have various impacts depending on the use of the analytical method.
For example, if the method is used for release testing, then the model should be high-impact. If an MSPC model is used for continuous process verification along with a traditional method for release testing, then the MSPC model would likely be classified as a medium-impact model. However, if an MSPC model is used to support a surrogate for a traditional release testing method in an RTRT approach, then the model would likely be classified as a high-impact model.
Data-driven models should be developed through appropriately designed experiments. These models are typically medium-impact or high-impact. For example, a feed forward model to adjust compression parameters on the basis of incoming material attributes could be classified as a medium-impact model. Developing and Implementing Models. The following steps, if applicable, can be followed in a sequential manner, but occasionally, it might be appropriate to repeat an earlier step, thus imparting an iterative nature to this process.
The overall steps are:. Defining the purpose of the model. Deciding on the type of modeling approach e. Selecting variables for the model; this is typically based on risk assessment, underlying physicochemical phenomena, inherent process knowledge, and prior experience.
Understanding the limitations of the model assumptions to: a. Correctly design any appropriate experiments; b. Interpret the model results; and c. Include appropriate risk-reduction strategies. Collecting experimental data to support model development. These data can be collected at laboratory, pilot, or commercial scale, depending on the nature of the model. It is important to ensure that variable ranges evaluated during model development are representative of conditions that would be expected during operation.
Developing model equations and estimating parameters, based on a scientific understanding of the process and collected experimental data. Validating the model, as appropriate see section V.
In certain cases, evaluating the impact of uncertainty in model prediction on product quality and, if appropriate, defining an approach to reduce associated residual risk e. Documenting the outcome of model development, including model assumptions, and developing plans for verification and update of the model throughout the lifecycle of the product. The level of documentation would be dependent on the impact of the model see section V.
Model validation is an essential part of model development and implementation. Once a model is developed and implemented, verification continues throughout the lifecycle of the product. The following elements can be considered for model validation and verification and generally are appropriate for high-impact models. In the case of well-established first principles-driven models, prior knowledge can be leveraged to support model validation and verification, if applicable.
The applicability of the elements listed below for medium-impact or low-impact models can be considered on a case-by-case basis.
In setting the acceptance criteria, variability in sampling procedure e.
U.S. Food and Drug Administration
Technological convergence is a tendency for technologies that were originally quite unrelated to become more closely integrated and even unified as they develop and advance. The concept is roughly analogous to convergent evolution in biological systems, such that for example the ancestors of whales became progressively more like fish in outward form and function, despite not being fish and not coming from a fish lineage. In technological convergence, a cardinal example to convey the concept is that telephones , television , and computers began as separate and mostly unrelated technologies but have converged in many ways into interrelated parts of a telecommunication and media industry underpinned by common elements of digital electronics and software. Such changes in the respective ecosystem open new trends, pathways, and opportunities in the following divergent phase of the process " Roco ,  Bainbridge and Roco .
Information technology is revolutionizing products. Once composed solely of mechanical and electrical parts, products have become complex systems that combine hardware, sensors, data storage, microprocessors, software, and connectivity in myriad ways. Information technology is revolutionizing products, from appliances to cars to mining equipment. Products once composed solely of mechanical and electrical parts have become complex systems combining hardware, sensors, electronics, and software that connect through the internet in myriad ways.
New Tech, New Threats, and New Governance Challenges: An Opportunity to Craft Smarter Responses?
Emerging technologies developed for commercial use are increasingly being used for defense, creating regulatory challenges. How can governments address these challenges while enabling innovation and growth? A swarm of drones patrols the battlespace, guided by sensors originally developed for smart factories. An artificial intelligence algorithm developed for online gaming steers military commanders toward smarter, faster decision-making. Ubiquitous cameras and ample cloud storage bring facial recognition to every street corner, but they can be used for both assessing threats in airports as well as to identify intelligence operatives. Subscribe to receive related content from Deloitte Insights. The foundations for these technologies were developed for commercial uses and are readily available for consumers on the open market. However, the acceleration in innovation and technology, particularly in the commercial sector, creates challenges for those who need to regulate them. There are innumerable examples of how commercial-origin technology can have unintended national security consequences—and how our current regulatory regime has not yet adapted for this new reality in order to keep such capabilities out of the hands of hostile actors. A precursor to protecting critical technologies is identifying what technologies are, in fact, critical.
Top 10 Technology Trends for 2020
Healthcare changes dramatically because of technological developments, from anesthetics and antibiotics to magnetic resonance imaging scanners and radiotherapy. Future technological innovation is going to keep transforming healthcare, yet while technologies new drugs and treatments, new devices, new social media support for healthcare, etc will drive innovation, human factors will remain one of the stable limitations of breakthroughs. No predictions can satisfy everybody; instead, this article explores fragments of the future to see how to think more clearly about how to get where we want to go. Technology drives healthcare more than any other force, and in the future it will continue to develop in dramatic ways.
Significant technological advances are being made across a range of fields, including information communications technology ICT ; artificial intelligence AI , particularly in terms of machine learning and robotics; nanotechnology; space technology; biotechnology; and quantum computing to name but a few. These breakthroughs are expected to be highly disruptive and bring about major transformative shifts in how societies function. The technological advances in question are driven by a digital revolution that commenced more than four decades ago. These innovations are centered on the gathering, processing, and analyzing of enormous reams of data emerging from the information sciences with implications for countless areas of research and development.
Internet of things
As emerging technologies drive new business and service models, governments must rapidly create, modify, and enforce regulations. The preeminent issue is how to protect citizens and ensure fair markets while letting innovation and businesses flourish. Subscribe to receive related content. Emerging technologies such as artificial intelligence AI , machine learning, big data analytics, distributed ledger technology, and the Internet of Things IoT are creating new ways for consumers to interact—and disrupting traditional business models.
They should be considered all together. The points to consider are not intended to be new guidance. They are intended to provide clarity to both industry and regulators and to facilitate the preparation, assessment, and inspection related to applications filed for marketing authorizations. The development approach should be adapted based on the complexity and specificity of product and process; therefore, applicants are encouraged to contact regulatory authorities regarding questions related to specific information to be included in their application. Using the Quality by Design QbD approach does not change regional regulatory requirements but can provide opportunities for more flexible approaches to meet them.
Privacy and Information Technology
Request a Demo. Enable rapid failure recovery and diversity switching. Centralize, track, and visualize the signal flow. Automate common time consuming and manual tasks. Connect to any equipment, regardless of type, vendor, or age. Reduce costly site visits with remote site management.
The Internet of Things IoT is a system of interrelated computing devices, mechanical and digital machines, objects, animals or people that are provided with unique identifiers UIDs and the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction. The definition of the Internet of Things has evolved due to the convergence of multiple technologies, real-time analytics , machine learning , commodity sensors , and embedded systems. In the consumer market, IoT technology is most synonymous with products pertaining to the concept of the "smart home", covering devices and appliances such as lighting fixtures, thermostats , home security systems and cameras, and other home appliances that support one or more common ecosystems, and can be controlled via devices associated with that ecosystem, such as smartphones and smart speakers. There are a number of serious concerns about dangers in the growth of IoT, especially in the areas of privacy and security , and consequently industry and governmental moves to begin to address these. The concept of a network of smart devices was discussed as early as , with a modified Coke vending machine at Carnegie Mellon University becoming the first Internet-connected appliance,  able to report its inventory and whether newly loaded drinks were cold or not.
How Smart, Connected Products Are Transforming Competition
В Нью-Йорке они задержались примерно на час. Вооруженная охрана встретила пленников на посадочной площадке - на западной площади - и сразу же конфисковала их рюкзаки, невзирая на громкие протесты Ричарда и Никки. На пути к Порту Ричард нес Никки на руках и едва успел восхититься своими любимыми небоскребами, вздымающимися над головой во тьме. Яхта, переправившая их через северную половину Цилиндрического моря, была копией тех увеселительных лодок, которые Накамура и его прихлебатели использовали на озере Шекспир.
Technology and the Future of Healthcare
Николь была весьма довольна. Она наконец одолела всю комнату по периметру без остановки. - Браво, - похвалил ее Орел, подходя к. - Просто сказочный прогресс.
Сити, хати, кю. - Вот тебе за то, что ты сделал с моим отцом, - Кэти приставила дуло к его лбу.
Какие это новости нельзя доверить Франц начал расхаживать по гостиной. Комната была со вкусом обставлена: черно-белая софа на двоих, под стать ей два кресла и несколько _произведений искусства_ на стенах и кофейном столике.
- Твоя квартира не прослушивается. - Ну, это ты должен сказать _мне_, мистер капитан полиции, - ответила Кэти. - Едва ли, Франц, - добавила она, поглядев на часы.
Когда мы возвратились в конференц-зал, меня принялись расспрашивать о пищеварительной системе человека. Вопросы были крайне сложными. шаг за шагом мы прошли весь цикл лимонной кислоты Кребса, обсудили основы биохимии человека, которую я едва помню (меня вновь поразило, насколько октопауки больше знают о людях, чем мы о них). Как всегда, мне ни разу не пришлось повторять ответ.
Какой день. Он начался со страдания, с печали о Бенджи.
На деле, лишь Элли _свободно_ владеет вашей речью. А я все еще учусь - день ото дня. - Я начинал эту работу, желая одолеть ту трудность, которую она предоставляет, а заодно заставить себя выучить ваш язык, - Ричард адресовал свои слова Геркулесу.
- На прошлой неделе мы с Николь как раз говорили о том, насколько нам нужно переводящее устройство.