Posts Tagged Digital transformation

Webinar: Agatha – Quality and Content Management Solution

Banner_Agatha Webinar

Webinar: Agatha – Quality and Content Management Solution

Arithmos with its partner Agatha Inc. is excited to invite you to a joint webinar. This webinar aims at presenting Agatha – a cloud-based Quality and Content Management tool for Life Sciences and Healthcare organizations. Agatha is dedicated to helping organizations such as hospitals, biotechnology, pharmaceutical and medical device companies as well as Contract Research Organizations optimize the management of their quality and clinical documentation and processes. The system is highly configurable, allowing for tailored customizations that fit the company’s workflow.

Click here to learn more about the webinar and register your attendance

Date and time:

Friday, April the 17th, 2020, 11:00 AM – 12:00 PM CEST.

The key learning outcomes will be:

  • How to use Agatha for the management of company’s quality and clinical documentation and processes
  • How to use a single tool order to streamline the collaboration between QA, Regulatory, and Clinical departments
  • Advantages of a pure cloud service compared to the service on premise

Presenters: 

  • Silvia Gabanti, Managing Director of Arithmos
  • Guillaume Gerard, Chief Operating Officer of Agatha Inc

Choosing the Right EDC: Advice from a Data Manager

EDC Data Management

Choosing the Right EDC: Advice from a Data Manager

How do you select the best Electronic Data Capture (EDC) system for your study? What are the must-have features and what are the nice-haves? We have asked Pedro M. Lledó, a Clinical Data Management professional with over 20 years experience, to share his tips for choosing the right EDC based on its functionality.

Key factors to consider

When you are looking for a new EDC system for a study, you should consider the following key factors:

  • Vendor – find a reliable and seasoned company, with years of experience. They know how to avoid the most common errors when it comes to selling and implementing an EDC.
  • Type of study – the EDC choice depends on the type of study and the type of users involved. You don’t always need to get the most expensive and powerful EDC on the market. For example, for Phase I or Observational studies you shouldn’t search for a complexity of an eCRF for an oncology study.
  • System functionalities, including how the system is hosted (cloud or on premises).

When choosing a system, make sure you involve all the teams you’ll need during the study. Talk to them in advance and let them know what the adoption of a new EDC system means. For instance, if you involve only IT and DM departments, they can choose a system which does not support partial SDV. Clinical Operations department will learn about the system right before the study. When they discover that the partial SDV is not available, they will be concerned, as it is very important for them and for the sponsor.

The features listed below will ensure that you have efficiency, data integrity, smooth workflow, and your independence in training clinical personnel.

EDC Must-Haves

When you have identified several EDC candidates, check if they correspond to the most important criteria. Your future EDC should be:

  • Compliant – it must be a system that follows 21 CRF part 11 rules, ensuring it is FDA and EMA compliant.
  • Internet browser agnostic – it should run in the most popular browsers.
  • Easy to program different types of queries, intra page, inter page/visits – it should be possible to address the queries not only to the investigator site, but also to CRAs, DMs, and MMs.
  • Allowing per user access control – every user, depending on the assigned role(s), should have access only to the allowed data or actions.
  • Flexible – you should be able to create on page queries and offline periodic listings and reports. This is important because you need to receive the warnings at the datapoint where the problem is located. In addition, you need some standard periodic listings to group all the queries by type, page, module etc.
  • Easy to monitor – this includes the presence of integrated reporting, standard study performance reports, KPIs, metrics. We need to see how people that are related to the data cleaning are performing.
  • Easy to master independently – alongside a user-friendly interface, it is important to also have on-line help resources.

EDC Nice-Haves

The functionalities listed above are critical for having an efficient EDC that allows you to capture data in a smart way. However, if you would like to reduce the number of errors in your data, further boost data integrity, and ease the life of your Data Managers, I suggest to look for an EDC that allows you to:

  • Easily configure register of data managers, CRAs, sites and user accounts.
  • Carry out partial source data verification (SDV monitoring). This function allows you to save the resources and focus only on the critical variables during the verification process.
  • Configure query workflow. It gives you additional flexibility and control when it comes to defining the query workflow, thus reducing such risks as overriding queries.
  • Use it also on portable devices with a nice page rendering. A lot of medical personnel use mobile devices for activities control and CRF data entry.
  • Optimize data management with dynamic CRF environment per protocol or patient data. In such EDC, different visits/pages or modules will appear/be hidden dynamically in a patient CRF. CRF will adjust automatically the number of pages or modules to the amount of information.
  • Gather from/share data with other systems, like eTMFs, CTMS, ePRO systems, patient wearable data management systems, PhV systems, BI tools and reporting systems, etc. This reduces the amount of effort during the data input and ensures data integrity.
  • Carry out training online through an e-Learning training module.

Don’t forget to ask about the technology layer behind the system. Trust a reliable and performant database, with a dynamic, quick page loading and rendering front end.

Finally, do not rush! Take your time to find the appropriate EDC. It will later save you time, money, and stress.

Good luck!

For further information about choosing the right EDC and our proprietary EDC solutions please contact us at info@arithmostech.com or click here.

Pedro Lledo Data ManagementAbout Pedro M. Lledó

Pedro M. Lledó is a physician by training who has been participating in clinical research projects for more than 20 years either as IT specialist, database administrator or clinical research data manager. Prior to joining Arithmos he has held leadership positions within CROs and biotechnology companies as Head of Data Management and Biometrics.

Digital Transformation in Life Sciences: an Insider Look

Silvia Gabanti Interview_2

Silvia Gabanti Interview_2

Digital Transformation in Life Sciences: an Insider Look

As the word “digital transformation” appears more and more often on the Life Sciences event agenda and in industry article titles, Arithmos has decided to look at this trend through the eyes of an industry professional. We sat down with Silvia Gabanti, Managing Director of Arithmos, to talk about how technology transforms clinical research, patient centricity and healthcare and what are the biggest challenges for going digital.

Silvia Gabanti has an impressive 15-year track record in the Life Sciences industry which started in the CRO environment where she was working with applications for pharmacovigilance and clinical trials.

Hello Silvia, thank you for joining us today. Digital transformation is a big concept what can be defined in numerous ways, how would you personally describe it?

I would say that Digital Transformation is a transformation of all the activities, processes and competencies in a way that allows us to harness the advantages of new digital technologies.

In order to approach digital transformation, all companies should think and act as technology companies, regardless of the industry they belong to.

I know it is not easy – it is a complete change of mindset! That is why such companies as Arithmos exist – we can act as consultants to bring this cultural shift in a company.

When did the relationship between digital transformation and Life Sciences start?

I am convinced that the industry started to change already two decades ago. It was not a drastic change though, but rather a slow one. It all started when technology became available not only for tech people but also for regular users. The Digital Transformation was on track when personal computers appeared in every home.

This was when the Life Sciences industry took notice and jumped on the new trend and started looking closely at technology.

The next Digital Transformation benchmark was at the end of the 2000s when social networks evolved. What started as entertainment actually had a significant impact on the Life Sciences industry. Just look at how companies are using social media for signal detection in pharmacovigilance or for recruiting patients to trials!

Life Sciences, like any other industry, mirrors our lives – technology is changing our lives, and we bring these changes to more complex fields like clinical research.

Technology became an extension of our resources and capabilities.

It definitely did. What is the manifestation of these changes that technology brings in Life Sciences?

I would say the key manifestation is information. Take the same social media we have been talking about – it is not a complex technology. What is exceptional about it is the huge flow of information that we have never seen before.

The amount of information we deal with now in the pharmaceutical environment is staggering. However, this information is what feeds the industry – information is the basis of the clinical research and Pharmacovigilance, and all this data and information allows us to make better decisions that result in better outcomes for patients.

Another manifestation of digital transformation is advanced technology. We are now developing tools that help us deal with this huge flow of information: – IoT, Artificial Intelligence, etc. The next step is Machine Learning, an extension of Artificial Intelligence.

Digital Transformation can brighten the future of Life Sciences, but for sure, there are constraints when it comes to these new technologies. What are the two biggest challenges in your opinion?

I would say that the biggest constraints are data security, privacy, and data integrity. It is of paramount importance to safeguard the privacy of data and to ensure that the data is reliable and accurate. And let’s not forget about compliance! Otherwise, there can be negative consequences for all the stakeholders involved: from the physician to the drug development companies, and most importantly the patient.

Over 50 percent of pharma companies reported data security breaches last year. If we are going to treat data as our most valuable asset, as it should be, we also need to protect it.

How can we ensure security and privacy?

Every entity that processes personal and/or sensitive data should think of security and privacy in a broader sense since privacy is not limited to only their system. They should see the whole picture.  Even if the patient data in the Clinical and/or Safety system is pseudo-anonymized, the risk of multiple breaches in different systems (even if indirect and remote) has to be taken into account and mitigated. Here is where we see continuously evolving technology adding to the complexity of security and privacy risk management. By evolving technology, I mean IoT, usage of personal devices in Clinical Trials, and so on.

Again, this requires a change in mindset and understanding the importance of investing in this area. Digital Transformation is not simply the implementation of new technology, it’s a structural change.

What about GDPR?

GDPR is something quite new in terms of regulations, but it has followed the privacy trend that has always existed in Life Sciences. Nevertheless, the new regulation lays the foundation for a more structured and coherent approach to data privacy and security.

What about data integrity?

Data integrity means the data must be reliable. Sounds simple, but in reality, it is a complex task. Here technology is essential: vendors should have technology solutions that allow for complete, consistent and accurate data outputs.

This means that companies must implement meaningful and effective strategies to manage their data integrity risks based on their process understanding and knowledge management of technologies and business models. What does Arithmos do to stay on the forefront of Digital Transformation in Life Sciences?

We leverage. For Arithmos, Digital Transformation is not a result, it is a process. We accompany our clients on this path: we help them to identify the need and then work together on transforming the processes and finding the right technology to satisfy this need.

Of course, we should not forget about change management. Digital Transformation is not possible without changing mentality and the business culture in general, and Arithmos can support with this. Our digital transformation starts internally, and we perform training and explain new approaches to all employees from upper management to operational, business and administrative resources. We also define a sustainable roadmap.

We believe in Digital Transformation and the innovative changes it brings to Life Sciences environment.

Digital Transformation with Arithmos

Do you want to integrate new technologies and processes? Is your company evaluating a digital health strategy? Arithmos works with companies to define a Digital Transformation journey that includes:

  • Disruptive Technologies – Digital Health and eClinical selection and consultancy: IoT/Wearables, eClinical (EDC, ePRO);
  • Process Management – Review and improvement of procedures and SOPs;
  • Oversight & Visual Analytics – Oversight platform, Business Intelligence tools, Visual Analytics, Statistical/Data Interpretation and Data Management;
  • Data Integrity & Security – Gap analysis for data security and GDPR compliance, Computer System Validation in GxP environment, necessary ISO certifications;
  • Industry Compliance – Regulatory guidance and compliance;
  • Data Science – Biostatistics, Statistical Programing, and Data Management;

Send us an RFI via our website to understand how Digital Transformation can be applied to your company!

Interested in more materials on Digital Transformation?

It’s Data Protection Day!

Data protection Day 2019

Data protection Day 2019

It’s Data Protection Day!

Did you know that January 28th is Data Protection Day? The Council of Europe launched this commemorative day in 2007, and two years later, the USA joined the initiative. We fully support this initiative, and as a technology company that operates in the Life Sciences sector, we recognize this important day by sharing six facts about data privacy in the healthcare sector.

Fact #1

The most significant and recent data privacy law is probably the EU General Data Protection Regulation, better known as GDPR. It is a set of more than 250 pages approved by the European Parliament, the Council of the European Union and the European Commission. The GDPR has replaced the previous Data Protection Directive 95/46/EC from 1995 and has introduced cohesive rules for ensuring that the EU population is aware of how their personal data is handled.

Fact #2

In regards to health data, GDPR defines three types of data that require special protection: data concerning health, genetic data, and biometric data.[1]

Fact #3

Back in 2017, 54% of healthcare professionals thought that the responsibility for getting medical records from one healthcare facility to another lied with healthcare professionals/facilities. However, the responsibility should lie with both patients and professionals/facilities (57%).[2] We wonder: how did the situation change in the last year and half?

Fact #4

In the USA, privacy and security of health data is governed by Health Insurance Portability and Accountability Act of 1996 (HIPAA) Privacy, Security, and Breach Notification Rules. They set the requirements for limits on how health information can be used and shared with others and how it should be kept secure with administrative, technical, and physical safeguards.

Fact #5

Speaking of American legislation, in 2018, American Congress attempted to enact a bill that could align 42 CFR Part 2’s standards with HIPAA. The draft legislation would have permitted providers to share information about patients subject to 42 CFR Part 2 for the purpose of treatment, payment, and operations.

Fact #6

Even though the notion of data privacy is often linked to the notion of security, security is not always sufficient to ensure privacy. Privacy can be defined as the ability to protect sensitive information about personally identifiable health care information, while security can be described as the protection against unauthorized access, with some including explicit mention of integrity and availability.[3]

There are many ways to ensure the security of health data, and one of them is opting for a partner that has implemented best practices in this area including internationally recognized certifications, such as ISO 27001. ISO 27001 is the most famous standard in the family providing requirements for an information security management system (ISMS). It guarantees, that a company maintains the confidentiality, integrity, and availability of personal health and patient data and information.

If you want to learn more about importance of ISO 27001 in healthcare sector, we invite you to have a look at this material.

We in Arithmos take great pride in honoring data privacy and security, and ensure that all our products and internal processes are compliant. We are also ISO 27001 certified, and we are thrilled to say that we have confirmed this status with a re-certification in December 2018.

Want to know more about privacy and security in the healthcare sector? Send your questions at info@arithmostech.com!  

[1] General Data Protection Regulation

[2] Future Health Index 2017

[3] Karim Abouelmehdi, Abderrahim Beni-Hessane, Hayat Khaloufi: Big healthcare data: preserving security and privacy

[Infographics] Five key trends in AI-Healthcare

AI in healthcare

Five key trends in AI-Healthcare

Healthcare is undergoing digital transformation, and now there are no doubts about it: technology has become its integral part, conquering more and more aspects of patient interaction, R&D and clinical trials. The most frequent word that you will now hear when it comes to healthcare digitalization is “AI” or “Artificial Intelligence”.

AI is said to be a game changer that could allow for reductions in healthcare costs as well as workload reduction for physicians which can result in clinical trial optimization and better early diagnostics. The growth predictions are staggering: McKinsey estimates AI to have the potential to create between $3.5T and $5.8T in value annually across nine business functions in 19 industries.*

We decided to look at what could be the key AI trends in healthcare that have the potential to revolutionize healthcare:

Arithmos always strives to be at the forefront of digital transformation in life sciences by applying technologies that satisfy the customer’s needs while achieving the best results in R&D, Clinical Research, Pharmacovigilance and Medical Project Management.

Are you planning to incorporate digital transformation in your company’s strategy? We would be glad to help you! Send us a request by filling in the contact form and let’s discuss how to introduce digital transformation in your life sciences strategy!

*Retrieved from Forbes “Sizing The Market Value Of Artificial Intelligence” on 01.10.2018.

Summary: conference “Artificial Intelligence and Clinical Research” (Milan) | What is the industry saying?

Artificial Intelligence in Clinical trials Milan

Summary: conference “Artificial Intelligence and Clinical Research” (Milan) | What is the industry saying?

Artificial Intelligence (AI) is a hot topic in the world of clinical trials, with researchers, academics and industry experts examining how it can “change the rules of the game”. Arithmos strives to be at the forefront of digital transformation in life sciences, so on the 18th of September we were present at the conference “Artificial Intelligence and Clinical Research” (Intelligenza artificiale e ricerca clinica) to get the latest updates from the industry. It took place at Politecnico di Milano, the largest technical university in Italy and looked at analyzing the possibility of simplifying the clinical research process with Artificial Intelligence.

The event featured such speakers as:

  • Massimo Beccaria, Managing Director Alfa Technologies International;
  • Giuseppe Recchia, Vice President Medical Scientific, GSK;
  • Matteo Matteucci, Associate Professor of Politecnico di Milano (Robotics, Cognitive Robotics, and Machine Learning);
  • Roberto Fantino, Presidente NAT Style;
  • Enrico G. Caiani: Associate Professor of Politecnico di Milano, Chairman WG e-Cardiology European Society of Cardiology, Docente eHealth and Bioengineering;
  • Giorgio Manfredi, CEO Rumbletumbleweed, CEO Occambee, Founder Forever Identity Inc., Advisor ISMC;
  • Maurizio Viviani, CEO Strong Artificial Intelligence;
  • Ettore Murciano, VP Channel Sales and Alliances, Loop AI Labs Inc;
  • Eugenio Santoro, Responsabile del laboratorio di informatica medica, Istituto di Ricerche Farmacologiche Mario Negri – IRCCS;
  • Sergio Scaccabarozzi, Head of Country Clinical Operations-Italy, Roche.

All the speeches represented very interesting insights from various points of view – research center, private company or university. What were some key points we took home? We first look at how the industry is being setup to look for AI solutions:

Giuseppe Recchia, Vice President Medical Scientific, GSK:

  • The future of clinical research will be defined between 2018 and 2020;
  • The whole revolution in clinical trials is about searching for a solution for faster development of the cure;
  • Everything in clinical trials revolves around patients and gives birth to such notions as patient centricity and patient engagement. With time how the patient views himself has also changed:
    • Patient now does his own research, using his/her health data;
    • Patients now have their own input, for example, they are involved in medicine R&D;
    • Patient-expert is a new concept, formed only recently. Such patients have the experience of the illness and expertise. For example, they could have had training or understanding of the research dynamics and the regulatory basis.
  • The aim of modernizing Clinical Trials is getting us to the cure faster. Why is the process so lengthy now? There are several reasons: low enrollment rates, retention problems, adherence (patients do not take meds and says he/she does), quality, costs.
  • What are the steps in clinical trial modernization?
    • First step is developing patient centricity:
    • Second step is connecting to the patient. It is extremely important now, as siteless clinical trials are being developed because patient spend more time at home than at the research site.
    • Third step is modernization in the field of wearables;
    • Fourth step is taming big data;
    • Fifth and last step is applying AI in clinical trials;
  • Right now no pharma company applies these technologies at 100%, however, big steps are already being taken in this direction.

Enrico G. Caiani: Associate Professor of Politecnico di Milano, Chairman WG e-Cardiology European Society of Cardiology, Docente eHealth and Bioengineering:

  • Why does health care need AI? There are several main reasons:
    • For the quantity of data and its complexity: at the moment each person generated 1100 TRB during his/her lifetime;
    • For the sake of patient safety;
    • For achieving higher efficiency in terms of time;
  • AI is capable of changing the future of medicines in all its aspects from administrative to clinical;
  • The demand for AI in the scientific society grows every year: in 2013 at ESC Congress there were only 3 AI presentations and in 2018 – already 69;
  • What prevents AI from being adopted right away in clinical practice?
    • Pathology is always complex, so here having a big dataset is of ultimate importance. This enlarges costs and times for the medical data production. Moreover, since healthcare datasets are not usually shared, the possibility of using joint datasets is not available.
    • The clinical evidence is not sufficient since now there is a limited amount of evidence in research literature that can prove that AI is a superior technique.
    • This, in turn, triggers another barrier for AI adoption: lack of transparency on training, lack of information on timing and content of updates, lack of reports on performance and eventual fails;
    • Last, but not the least: the definition of ethical principles in AI is missing. In order to proceed with AI adoption, it should be clarified how AI can influence doctor-patient relations and decide who is responsible for errors caused by AI.

Eugenio Santoro, Responsabile del laboratorio di informatica medica, Istituto di Ricerche Farmacologiche Mario Negri – IRCCS:

  • What should be done in order to use AI in clinical research?
    • A structured approach should be implemented, as 80% of the data generated every day is not structured. Right now a huge amount of data is produced due to the use of smartphones, IoT and wearables, which has no formal system. The situation got escalated in the last 2 years – during which 90% of the world data was generated.
  • What is the potential of AI in healthcare?
    • Prevention and predictive models;
    • Early diagnosis;
    • Machine learning and chatbot;
    • Analyses of disease cause-effect, also called epidemiology 2.0. AI is employed here for finding possible logical connections between potential cause and effect;
    • Drug Discovery and clinical trials;
  • How can AI improve clinical research in particular:
    • Aggregation and synthesis of information: AI allows intuitive searches in the world biomedical research data including biomedical databases;
    • Recruiting for clinical trials: AI can analyze medical records and other unstructured documents to find the appropriate patients for clinical trials and can accelerate recruitment to complete the clinical trial faster.
    • Understanding the mechanism of disease: AI can analyzes databases, connecting published literature, experimental data, and clinical data and allows researchers to get insight into how the disease mechanism operates;
    • Repurposing existing drugs: AI can synthesize knowledge from multiple biomedical sources and find new indications for existing drugs;
    • Generate novel drug candidates: AI can generate novel drug candidates faster;
    • Optimize clinical trials: AI can analyze data of participants and reduce the dropout rates through personalized communication;
    • Publish data: AI can write a draft of a scientific manuscript based on provided data;
    • Sentiment analysis: AI can assist in the pharmacovigilance process by monitoring the adverse events and help with the study of public health, such as infection and drug abuse.

Workshop: Industry 4.0 and Life Sciences

Workshop Industry 4.0

Industry 4.0 Life Sciences

Workshop: Industry 4.0 and Life Sciences

This June, experts in the Life Sciences industry gathered in Milan to participate in a workshop on “Industry 4.0: The New Challenges for Project Planning and Oversight in the Life Sciences Industry”. The workshop was a result of joint efforts between our Arithmos team and LS Academy and was organized in order to peek into changes triggered by Industry 4.0.

Industry 4.0 is a recent concept that encompasses all the processes of automatizations and emerging cyber-physical systems in different industries. Life Science is among the areas most affected by these changes due to its willingness to adopt new technologies and its responsiveness to new trends. During our workshop, we covered different aspects of the Life Sciences industry that are affected by Industry 4.0.

Workshop agenda

We have invited a number of Key Opinion Leaders from the Pharma and Life Sciences fields to share their experience and ideas on Industry 4.0. Here are the topics they have covered during the workshop:

  • IoT and Big Data: advantages and opportunities of eHealth technologies in Life Sciences Sector.
  • New challenges for Human Resources in Industry 4.0: Management time planning research results and their structure.
  • Sponsor Oversight Management: Effective use of third party technology.
    • Speaker: Heike Schoen, Managing Director and Co-Founder at LUMIS International GmbH;
  • New model of Industry 4.0: Altea UP. Instruments and technologie for the pharma process governance.
  • Implementation strategy of ClinOps system: challenges and choices.
    • Speaker: Daniele Segagni, Group ICT Global Business Process and Application Specialist, Chiesi Group
  • How new technologies are changing patient relations: from the SEO era to IA and chatbot.
    • Speaker: Matteo Nicolosi, Web Content Developer at Istituto Clinico Humanitas;
  • How intelligent automation is reshaping the workforce landscape.
    • Speaker: Andrea Melison, Senior Manager Business Service at KPMG Italy.

Best quotes of the workshop

  • “Blending IoT, Big Data and AI in clinical trials processes can greatly improve the competitiveness of CROs and Pharma/Medical Companies, while at the same time lowering the costs of clinical research and facilitation the invention and validation of new medical products and services that will revolutionize healthcare in the years to come.” – Paolo Morelli
  • “Digital revolution has positive effect if it helps employers to compress time needed for standardized activities and relocate it to work activities that require non-standard approach.” – Roberto Bugatti
  • “Company should set adequate extended and shared IT Governance structure, which ensures that the company data is managed correctly.” – Pierluigi De Rosa
  • “Real-World Evidence could be used from R&D departments to support regulatory submissions for additional drug indications and to inform new drug development.” – Daniele Segagni”
  • “Robotic Process Automation and digital labor can be scaled much more quickly and cost effectively than traditional IT implementations.” – Andrea Melison

Want to get expert content from the workshop? Send us a request via our online contact form!

8 Best Quotes from “Process Automation & Performance Improvement” Workshop – Milan 13th July, Talent Garden

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