China Pharmaceutical Robots Market Analysis

China Pharmaceutical Robots Market Analysis


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China Pharmaceutical Robots Market is projected to grow from $xx Mn in 2022 to $xx Mn by 2030, registering a CAGR of xx% during the forecast period of 2022 - 2030. The market for pharmaceutical robots is rising due to increasing number of medical research activities, increased emphasis on efficiency and productivity of pharmaceuticals. Kawasaki Heavy Industries Ltd. (Japan), FANUC Corporation (Japan), KUKA AG (Germany), Mitsubishi Electric Corporation (Japan), ABB (Switzerland), Denso corporation (Japan), etc. are some of the key players in this market.

ID: IN10CNPH370 CATEGORY: Pharmaceuticals GEOGRAPHY: China AUTHOR: Saloni Shah

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China Pharmaceutical Robots Market Analysis Summary

China Pharmaceutical Robots Market is valued at around $12.8 Mn in 2022 and is projected to reach $33.1 Mn by 2030, exhibiting a CAGR of 12.7% during the forecast period 2023-2030.

Artificial intelligence robots are employed in a wide range of applications including pharmaceutical robots. Pharmaceutical robots provide a high level of automation and reduce the need for manual labor or human input, saving time and lowering human effort. This indicates that pharmaceutical robots offer a higher level of automation and accuracy.

Market Dynamics

Market Growth Drivers

Increasing number of medical research activities, increased emphasis on efficiency and productivity of pharmaceuticals, complex drug formulations and personalized medicine development requiring precise processes which are offered by robots, increasing drug demand and aging population, Product packaging and serialization demands which can be easily fulfilled by pharmaceutical robots, workforce safety as robots can handle tasks that involve exposure to toxic substances. All these factors act as market growth drivers.

Market Restraints

Software problems involving medical robots- Pharmaceutical robots are controlled by computer programs, which can abruptly stop working at any time. It can take a lot of time to install software updates and secure the machine to the pharmacy's record management system, and these tasks must be completed correctly to prevent issues in the future.

A high initial investment in setting up pharmaceutical robots, complexity and customization of a wide range of drug formulations, lack of skilled workforce to operate pharmaceutical robots, and safety concerns associated with robots. All these factors act as market growth restraints.

Competitive Landscape

Key Players

  • Kawasaki Heavy Industries Ltd.
  • FANUC Corporation
  • KUKA AG
  • Mitsubishi Electric Corporation
  • ABB
  • DENSO CORPORATION
  • Seiko Epson Corporation
  • Marchesini Group S.p.A
  • Universal Robots A/S
  • Yaskawa Electric Corporation
  • Shibuya Corporation
  • Remtec Automation, LLC
  • Gridbots Technologies Private Limited
  • Lockheed Martin Corporation
  • Robert Bosch GmbH

Notable Deals in the Pharmaceutical Robots Market

In 2021, ABB introduced two new robots to its lineup in response to the growing need for automated manufacturing. According to reports, the company's sales of robots have increased by about 90% to keep up with the demand in the pharmaceutical sector.

1. Executive Summary
1.1 Disease Overview
1.2 Global Scenario
1.3 Country Overview
1.4 Healthcare Scenario in Country
1.5 Patient Journey
1.6 Health Insurance Coverage in Country
1.7 Active Pharmaceutical Ingredient (API)
1.8 Recent Developments in the Country

2. Market Size and Forecasting
2.1 Epidemiology of Disease
2.2 Market Size (With Excel & Methodology)
2.3 Market Segmentation (Check all Segments in Segmentation Section)

3. Market Dynamics
3.1 Market Drivers
3.2 Market Restraints

4. Competitive Landscape
4.1 Major Market Share

4.2 Key Company Profile (Check all Companies in the Summary Section)

4.2.1 Company
4.2.1.1 Overview
4.2.1.2 Product Applications and Services
4.2.1.3 Recent Developments
4.2.1.4 Partnerships Ecosystem
4.2.1.5 Financials (Based on Availability)

5. Reimbursement Scenario
5.1 Reimbursement Regulation
5.2 Reimbursement Process for Diagnosis
5.3 Reimbursement Process for Treatment

6. Methodology and Scope

Market Segmentations For sexy Pharmaceutical Robots Market

By Product Type

  • Traditional Robots
  • Collaborative Pharmaceutical Robots

By Application

  • Picking and Packaging,
  • Inspection of Pharmaceutical Drugs,
  • Laboratory Applications

By End User

  • Pharmaceutical Companies
  • Research Laboratories

Methodology for Database Creation

Our database offers a comprehensive list of healthcare centers, meticulously curated to provide detailed information on a wide range of specialties and services. It includes top-tier hospitals, clinics, and diagnostic facilities across 30 countries and 24 specialties, ensuring users can find the healthcare services they need.​

Additionally, we provide a comprehensive list of Key Opinion Leaders (KOLs) based on your requirements. Our curated list captures various crucial aspects of the KOLs, offering more than just general information. Whether you're looking to boost brand awareness, drive engagement, or launch a new product, our extensive list of KOLs ensures you have the right experts by your side. Covering 30 countries and 36 specialties, our database guarantees access to the best KOLs in the healthcare industry, supporting strategic decisions and enhancing your initiatives.

How Do We Get It?

Our database is created and maintained through a combination of secondary and primary research methodologies.

1. Secondary Research

With many years of experience in the healthcare field, we have our own rich proprietary data from various past projects. This historical data serves as the foundation for our database. Our continuous process of gathering data involves:

  • Analyzing historical proprietary data collected from multiple projects.
  • Regularly updating our existing data sets with new findings and trends.
  • Ensuring data consistency and accuracy through rigorous validation processes.

With extensive experience in the field, we have developed a proprietary GenAI-based technology that is uniquely tailored to our organization. This advanced technology enables us to scan a wide array of relevant information sources across the internet. Our data-gathering process includes:

  • Searching through academic conferences, published research, citations, and social media platforms
  • Collecting and compiling diverse data to build a comprehensive and detailed database
  • Continuously updating our database with new information to ensure its relevance and accuracy

2. Primary Research

To complement and validate our secondary data, we engage in primary research through local tie-ups and partnerships. This process involves:

  • Collaborating with local healthcare providers, hospitals, and clinics to gather real-time data.
  • Conducting surveys, interviews, and field studies to collect fresh data directly from the source.
  • Continuously refreshing our database to ensure that the information remains current and reliable.
  • Validating secondary data through cross-referencing with primary data to ensure accuracy and relevance.

Combining Secondary and Primary Research

By integrating both secondary and primary research methodologies, we ensure that our database is comprehensive, accurate, and up-to-date. The combined process involves:

  • Merging historical data from secondary research with real-time data from primary research.
  • Conducting thorough data validation and cleansing to remove inconsistencies and errors.
  • Organizing data into a structured format that is easily accessible and usable for various applications.
  • Continuously monitoring and updating the database to reflect the latest developments and trends in the healthcare field.

Through this meticulous process, we create a final database tailored to each region and domain within the healthcare industry. This approach ensures that our clients receive reliable and relevant data, empowering them to make informed decisions and drive innovation in their respective fields.

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Last updated on: 27 February 2024
Updated by: Anish Swaminathan

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