Why does the pharmaceutical industry need blockchain?

Maciej Zieliński

05 Jun 2020
Why does the pharmaceutical industry need blockchain?

How does blockchain help us to solve the problems faced by the modern health care? In an interview with Nextrope Muffie Fulton, Sr. Director of Pharma Solutions at Chronicled, an American company behind MediLedger, explains why the use of this technology is a breakthrough in medicine distribution.

Launched in 2017, MediLedger is building a decentralised and configurable drug supply chain management system based on blockchain technology. It introduces innovative solutions for regulating product traceability and controlling all processes related to the supply chain.

Medi Ledger brings together leading players in the pharmaceutical industry to form an industry-wide network of permissioned blockchains based on open standards and specifications. It has been developed to give pharmaceutical partners the opportunity to keep pace with rapidly changing regulations and to find better ways to cooperate within a common ecosystem.

Why do you think the pharmaceutical industry needs Blockchain technology and how is it superior to current solutions?

Two of the biggest concerns in the health care are safety and privacy. Patient and drug safety are always top of mind, and the need to secure the drug supply chain is paramount.
Data privacy is important for individual patients, but it is also very important for companies. Companies need to ensure their internal data and business intelligence data remain secure, while needing to share certain pieces of data with their trading partners.
Blockchain as a component in a private, permissioned, industry wide network is a great tool to allow companies to share information in a directed, confidential manner.
Shared, yet confidential, industry master data has the power to dramaticall improve the efficiency of many processes including supply chain, finance, procurement, and clinical trials.

Do you think that in the near future the demand for solutions enabling tracking drug supply chains will increase?

Certainly. Companies are implementing different pieces of the Drug Supply Chain Securities Act and are seeing the value of visibility. In addition, companies want to get more value out of regulatory driven implementations. We get requests daily from people and companies who want to build on the functionality from product verification to do everything from temperaturę tracking to dispeners who want to start verifying druges even before the DSCSA deadline because they see the business value. Also, as we near the deadlines for the full DSCSA confidential change of ownership requirements in 2023, patients will begin to learn about the fact that the drug supply chain is being more closely monitored and will want to share in that visibility. Right now they can see what step of the supply their book is in while it’s being delivered to tchem, and they are going to expect to have that same level of visibility for something as important as their medicines.

How do Chronicled solutions protect consumers and producers from counterfeit and diversion?

Our Product Verification Solution connects distributors and manufacturers, allowing distributors to scan the barcode on a pharmaceutical and the manufacturer can respond in under a second, verifying that the product identifiers are the same as the manufacturer created. If there i sany discrepancy, the distributor is able to isolate the product and notify the manufacturer. This helps to identify counterfeit product in the supply chain and eliminate it.

In your opinion, which business models can benefit the most from blockchian implementation?

Any business that is data intensive and trade intensive will benefit from blockchain, especially where privacy and interdependent processes within the industry are paramount.

What are the biggest challenges while developing a Blockchain products?

In pharma, one of the biggest challenges is the understanding of blockchain as a technology and the willingness to implement a solution that is seen as unproven. This is changing quickly, as many large companies now have innovation groups, or even specific blockchain groups, within their IT departments. In addition, companies are starting to understand that blockchain is simply a tool which opens up a world of possibilities in solving business problems.

Do you have any advice to entrepreneurs just starting in the Blockchain industry.

Focus on solutions to real business problems, and not the shiny new technology.

What is your vision for Blockchain development as an industry in the next 5 years?

We foresee industry wide alignment and the next phase of ERP becoming IRP, Industry Resource Planning. With the ability to strategically share confidential data, get alignment on and enforcement of business rules across the industry, and having the ability to have an entire industry in a shared yet private network, frictionless trade will result in efficiencies and savings for business and patients.

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Master UI Component Creation with AI: The Ultimate Guide for Developers

Gracjan Prusik

24 Mar 2025
Master UI Component Creation with AI: The Ultimate Guide for Developers

Introduction

Modern frontend development is evolving rapidly, and creating UI components with AI tools is helping developers save time while enhancing interface quality. With AI, we can not only speed up the creation of UI components but also improve their quality, optimize styles, and ensure better accessibility.

This article explores how creating UI components with AI is transforming frontend development by saving time and improving workflows. Specifically, we will discuss:

  • Generating components from images,
  • AI for style analysis and optimization,
  • Automatic style conversion and code migration,
  • AI in generating UI animations.

Creating UI Components with AI from Images

One of the interesting applications of AI in frontend development is the ability to generate components from an image. AI can recognize the structure of the interface and generate HTML/CSS or JSX code that matches the provided image. One of the most popular tools for UI creation is Lovable.

For testing, let's see how the tool performs in creating a simple contact form from the page you are currently on, which is Nextrope.

Query:

"Recreate the image I've sent you in Next.js using CSS."

Sample image used in the query:

The result received:

Tworzenie komponentów UI - Wygenerowany widok

Lovable did an excellent job transforming the image into code. The view is fully responsive. It’s important to remember that the more precise the request, the better the AI will replicate the expected view. However, even with a simple command, the tool performed surprisingly well.

Of course, AI has its limitations. It still makes quite a few mistakes. The generated code still requires review and fixes from the developer, but in some cases, the entire process is significantly sped up—correcting the code often takes less time than creating the component from scratch.

Optimizing UI Components with AI Tools for Style Improvements

This problem of inaccurate code reproduction by AI can be partially addressed by using it to analyze and improve styles. Tools like ChatGPT, DeepSeek and Claude are capable of not only generating code but also diagnosing CSS errors and suggesting why a particular style might not be working as expected.

Simple example: Why is the div not centered?

Query: "Why is this div not centered?"

AI analyzes the code and provides the following response:

Problem: The parent container does not have a defined width or display: flex.
Solution: Add the appropriate styles to the parent container.

.parent {
  display: flex;
  justify-content: center;
  align-items: center;
  width: 100vw;
  height: 100vh;
}

AI for Automatic Style Conversion and Code Migration in UI Components

AI can assist with style conversion between different technologies, such as transferring code from traditional CSS to Styled Components or Tailwind CSS.

Let's assume we have a style written in traditional CSS:

.button {
  background-color: blue;
  color: white;
  padding: 10px 20px;
  border-radius: 5px;
  transition: background-color 0.3s ease;
}

.button:hover {
  background-color: darkblue;
}

We can use AI for automatic conversion to Styled Components:

import styled from "styled-components";

const Button = styled.button`
  background-color: blue;
  color: white;
  padding: 10px 20px;
  border-radius: 5px;
  transition: background-color 0.3s ease;

  &:hover {
    background-color: darkblue;
  }
`;

export default Button;

AI can also assist in migrating code between frameworks, such as from React to Vue or from CSS to Tailwind.

This makes style migration easier and faster.

How AI Enhances UI Animation Creation

Animations are crucial for enhancing user experience in interfaces, but they are not always provided in the project specification. In such cases, developers have to come up with how the animations should look, which can be time-consuming and require significant creativity. AI, in this context, becomes helpful because it can automatically generate CSS animations or animations using libraries like Framer Motion, saving both time and effort.

Example: Automatically Generated Button Animation

Suppose we need to add a subtle scaling animation to a button but don't have a ready-made animation design. Instead of creating it from scratch, AI can generate the code that meets our needs.

Code generated by AI:

import { motion } from "framer-motion";

const AnimatedButton = () => (
  <motion.button
    whileHover={{ scale: 1.1 }}
    whileTap={{ scale: 0.9 }}
    className="bg-blue-500 text-white px-4 py-2 rounded-lg"
  >
    Press me
  </motion.button>
);

In this way, AI accelerates the animation creation process, providing developers with a simple and quick option to achieve the desired effect without the need to manually design animations from scratch.

Summary

AI significantly accelerates the creation of UI components. We can generate ready-made components from images, optimize styles, transform code between technologies, and create animations in just a few seconds. Tools like ChatGPT, DeepSeek, Claude and Lovable are a huge help for frontend developers, enabling faster and more efficient work.

In the next part of the series, we will take a look at:

If you want to learn more about how AI is impacting the entire automation of frontend processes and changing the role of developers, check out our blog article: AI in Frontend Automation – How It's Changing the Developer's Job?

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AI in Real Estate: How Does It Support the Housing Market?

Miłosz Mach

18 Mar 2025
AI in Real Estate: How Does It Support the Housing Market?

The digital transformation is reshaping numerous sectors of the economy, and real estate is no exception. By 2025, AI will no longer be a mere gadget but a powerful tool that facilitates customer interactions, streamlines decision-making processes, and optimizes sales operations. Simultaneously, blockchain technology ensures security, transparency, and scalability in transactions. With this article, we launch a series of publications exploring AI in business, focusing today on the application of artificial intelligence within the real estate industry.

AI vs. Tradition: Key Implementations of AI in Real Estate

Designing, selling, and managing properties—traditional methods are increasingly giving way to data-driven decision-making.

Breakthroughs in Customer Service

AI-powered chatbots and virtual assistants are revolutionizing how companies interact with their customers. These tools handle hundreds of inquiries simultaneously, personalize offers, and guide clients through the purchasing process. Implementing AI agents can lead to higher-quality leads for developers and automate responses to most standard customer queries. However, technical challenges in deploying such systems include:

  • Integration with existing real estate databases: Chatbots must have access to up-to-date listings, prices, and availability.
  • Personalization of communication: Systems must adapt their interactions to individual customer needs.
  • Management of industry-specific knowledge: Chatbots require specialized expertise about local real estate markets.

Advanced Data Analysis

Cognitive AI systems utilize deep learning to analyze complex relationships within the real estate market, such as macroeconomic trends, local zoning plans, and user behavior on social media platforms. Deploying such solutions necessitates:

  • Collecting high-quality historical data.
  • Building infrastructure for real-time data processing.
  • Developing appropriate machine learning models.
  • Continuously monitoring and updating models based on new data.

Intelligent Design

Generative artificial intelligence is revolutionizing architectural design. These advanced algorithms can produce dozens of building design variants that account for site constraints, legal requirements, energy efficiency considerations, and aesthetic preferences.

Optimizing Building Energy Efficiency

Smart building management systems (BMS) leverage AI to optimize energy consumption while maintaining resident comfort. Reinforcement learning algorithms analyze data from temperature, humidity, and air quality sensors to adjust heating, cooling, and ventilation parameters effectively.

Integration of AI with Blockchain in Real Estate

The convergence of AI with blockchain technology opens up new possibilities for the real estate sector. Blockchain is a distributed database where information is stored in immutable "blocks." It ensures transaction security and data transparency while AI analyzes these data points to derive actionable insights. In practice, this means that ownership histories, all transactions, and property modifications are recorded in an unalterable format, with AI aiding in interpreting these records and informing decision-making processes.

AI has the potential to bring significant value to the real estate sector—estimated between $110 billion and $180 billion by experts at McKinsey & Company.

Key development directions over the coming years include:

  • Autonomous negotiation systems: AI agents equipped with game theory strategies capable of conducting complex negotiations.
  • AI in urban planning: Algorithms designed to plan city development and optimize spatial allocation.
  • Property tokenization: Leveraging blockchain technology to divide properties into digital tokens that enable fractional investment opportunities.

Conclusion

For companies today, the question is no longer "if" but "how" to implement AI to maximize benefits and enhance competitiveness. A strategic approach begins with identifying specific business challenges followed by selecting appropriate technologies.

What values could AI potentially bring to your organization?
  • Reduction of operational costs through automation
  • Enhanced customer experience and shorter transaction times
  • Increased accuracy in forecasts and valuations, minimizing business risks
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Want to implement AI in your real estate business?

Nextrope specializes in implementing AI and blockchain solutions tailored to specific business needs. Our expertise allows us to:

  • Create intelligent chatbots that serve customers 24/7
  • Implement analytical systems for property valuation
  • Build secure blockchain solutions for real estate transactions
Schedule a free consultation

Or check out other articles from the "AI in Business" series